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  • 2701.
    Zhang, Yanqing
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Constructing Swedish Fashion Identity: Svenskt Mode (Swedish Fashion): 2000–2015, Sven-Harry’s Art Museum, Stockholm, May 23–August 31, 20142016In: Fashion theory, ISSN 1362-704X, E-ISSN 1751-7419, Vol. 20, no 4, p. 475-484Article, book review (Other academic)
    Abstract [en]

    This is an exhibition review article. It describes the goal, the curatorship, display and exhibited objects. The exhibition focuses on Swedish fashion design and treats fashion as something in relation to art. It analyzes the exhibition as part of institutionalization of Swedish fashion system. Understanding fashion as a system rather than material clothing is the key point here.

  • 2702.
    Zhang, Yanqing
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Juhlin, Oskar
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Fashion as System or Action Net in ‘Fashion in All Things’: a Case in Color Design of Mobile Phones2012In: Fashion: Exploring Critical Issues / [ed] Barbara Brownie, Laura Petican, Johannes Reponen, Oxford: Inter-Disciplinary Press, 2012, no 1, p. 263-270Chapter in book (Other academic)
    Abstract [en]

    Contemporary fashion has permeated into all things in life beyond clothes. Recently, fashion theories take on interests in organization and system. Kawamura proposes a fashion system through which clothing is transformed into the idea of fashion. Can this fashion system be used to analyze other things in fashion? We present a study using mobile phone, one of the most intimate gadgets to people, as a way to approach ‘fashion in all things’. We chose the color as a way to study the fashion aspect in mobile design. Through the empirical study, we find that the decision making of color in mobile industry is a collective process. It is greatly influenced by technology, materials, consumer lifestyle and trend. The trendy colors in mobile design are not defined by certain cultural or social institutions, but formulated by actions conducted by various actors in certain social context. Our study shows that fashion can embrace more than Kawamura’s system, e.g. the action net of color design in mobile technology. Although mobile design shares some similarities with clothing fashion, the concept of fashion-ology is very Parisian and deals with only clothing. It is not fully applicable to mobile industry. If we want to use a fashion system that can apply to fashion in all things, we should revisit the theory to reveal the general characteristics of the fashion world or build smaller theory for each category.

  • 2703.
    Zhang, Yanqing
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Juhlin, Oskar
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    The “life and death” of great Finnish fashion phone: A periodization of changing styles in Nokia phone design between 1992 and 20132016In: Mobile Media & Communication, ISSN 2050-1579, Vol. 4, no 3, p. 385-404Article in journal (Refereed)
    Abstract [en]

    Visual aesthetics is an essential part of our experience of mobile devices, but the ways in which it is accounted for in design have largely been overlooked. We investigate whether an aesthetization of mobile design is taking place and, if so, how it is being pursued through institutional practices in organizations. We conduct a visual analysis of all Nokia phone releases between 1992 and 2013 complemented by an interview series with key actors. The study reveals a continuous increase in aesthetic variation between 1998 and 2008, which is visible in the variation of colors, forms and materials. The period between 2003 and 2008, which we term the Grand period, marks the peak of aesthetization of Nokia’s devices. It exhibits great variation, and is visibly similar to aesthetics in the fashion industry. With the introduction of the slate form, we see a decrease in visual variation between 2009 and 2013. The interviews reveal how the visual design was driven by organizational strategies, such as customer segmentation in general, and an orientation toward the fashion industry, e.g. in the creation of a fashion segment. The study reveals how aesthetic variation is weaved into a complex innovation system with sometimes conflicting demands deriving from e.g. technology and user interaction.

  • 2704.
    Zhao, Jing
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Learning Predictive Models from Electronic Health Records2017Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    The ongoing digitization of healthcare, which has been much accelerated by the widespread adoption of electronic health records, generates unprecedented amounts of clinical data in a readily computable form. This, in turn, affords great opportunities for making meaningful secondary use of clinical data in the endeavor to improve healthcare, as well as to support epidemiology and medical research. To that end, there is a need for techniques capable of effectively and efficiently analyzing large amounts of clinical data. While machine learning provides the necessary tools, learning effective predictive models from electronic health records comes with many challenges due to the complexity of the data. Electronic health records contain heterogeneous and longitudinal data that jointly provides a rich perspective of patient trajectories in the healthcare process. The diverse characteristics of the data need to be properly accounted for when learning predictive models from clinical data. However, how best to represent healthcare data for predictive modeling has been insufficiently studied. This thesis addresses several of the technical challenges involved in learning effective predictive models from electronic health records.

    Methods are developed to address the challenges of (i) representing heterogeneous types of data, (ii) leveraging the concept hierarchy of clinical codes, and (iii) modeling the temporality of clinical events. The proposed methods are evaluated empirically in the context of detecting adverse drug events in electronic health records. Various representations of each type of data that account for its unique characteristics are investigated and it is shown that combining multiple representations yields improved predictive performance. It is also demonstrated how the information embedded in the concept hierarchy of clinical codes can be exploited, both for creating enriched feature spaces and for decomposing the predictive task. Moreover, incorporating temporal information leads to more effective predictive models by distinguishing between event occurrences in the patient history. Both single-point representations, using pre-assigned or learned temporal weights, and multivariate time series representations are shown to be more informative than representations in which temporality is ignored. Effective methods for representing heterogeneous and longitudinal data are key for enhancing and truly enabling meaningful secondary use of electronic health records through large-scale analysis of clinical data.

  • 2705.
    Zhao, Jing
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Temporal weighting of clinical events in electronic health records for pharmacovigilance2015In: 2015 IEEE International Conference on Bioinformatics and Biomedicine: Proceedings / [ed] Jun (Luke) Huan et al., IEEE Computer Society, 2015, p. 375-381Conference paper (Refereed)
    Abstract [en]

    Electronic health records (EHRs) have recently been identified as a potentially valuable source for monitoring adverse drug events (ADEs). However, ADEs are heavily under- reported in EHRs. Using machine learning algorithms to automatically detect patients that should have had ADEs reported in their health records is an efficient and effective solution. One of the challenges to that end is how to take into account temporality when using clinical events, which are time stamped in EHRs, as features for machine learning algorithms to exploit. Previous research on this topic suggests that representing EHR data as a bag of temporally weighted clinical events is promising; however, how to assign weights in an optimal manner remains unexplored. In this study, nine different temporal weighting strategies are proposed and evaluated using data extracted from a Swedish EHR database, where the predictive performance of models constructed with the random forest learning algorithm is compared. Moreover, variable importance is analyzed to obtain a deeper understanding as to why a certain weighting strategy is favored over another, as well as which clinical events undergo the biggest changes in importance with the various weighting strategies. The results show that the choice of weighting strategy has a significant impact on the predictive performance for ADE detection, and that the best choice of weighting strategy depends on the target ADE and, specifically, on its dose-dependency.

  • 2706.
    Zhao, Jing
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Henriksson, Aron
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Learning temporal weights of clinical events using variable importance2016In: BMC Medical Informatics and Decision Making, ISSN 1472-6947, E-ISSN 1472-6947, Vol. 16, no Suppl. 2, article id 71Article in journal (Refereed)
    Abstract [en]

    Background: Longitudinal data sources, such as electronic health records (EHRs), are very valuable for monitoring adverse drug events (ADEs). However, ADEs are heavily under-reported in EHRs. Using machine learning algorithms to automatically detect patients that should have had ADEs reported in their health records is an efficient and effective solution. One of the challenges to that end is how to take into account the temporality of clinical events, which are time stamped in EHRs, and providing these as features for machine learning algorithms to exploit. Previous research on this topic suggests that representing EHR data as a bag of temporally weighted clinical events is promising; however, the weights were in that case pre-assigned according to their time stamps, which is limited and potentially less accurate. This study therefore focuses on how to learn weights that effectively take into account the temporality and importance of clinical events for ADE detection. Methods: Variable importance obtained from the random forest learning algorithm is used for extracting temporal weights. Two strategies are proposed for applying the learned weights: weighted aggregation and weighted sampling. The first strategy aggregates the weighted clinical events from different time windows to form new features; the second strategy retains the original features but samples them by using their weights as probabilities when building each tree in the forest. The predictive performance of random forest models using the learned weights with the two strategies is compared to using pre-assigned weights. In addition, to assess the sensitivity of the weight-learning procedure, weights from different granularity levels are evaluated and compared. Results: In the weighted sampling strategy, using learned weights significantly improves the predictive performance, in comparison to using pre-assigned weights; however, there is no significant difference between them in the weighted aggregation strategy. Moreover, the granularity of the weight learning procedure has a significant impact on the former, but not on the latter. Conclusions: Learning temporal weights is significantly beneficial in terms of predictive performance with the weighted sampling strategy. Moreover, weighted aggregation generally diminishes the impact of temporal weighting of the clinical events, irrespective of whether the weights are pre-assigned or learned.

  • 2707.
    Zhao, Jing
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Henriksson, Aron
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Asker, Lars
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Boström, Henrik
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Detecting Adverse Drug Events with Multiple Representations of Clinical Measurements2014In: 2014 IEEE International Conference on Bioinformatics and Biomedicine (BIBM): Proceedings, IEEE Computer Society, 2014, p. 536-543Conference paper (Refereed)
    Abstract [en]

    Adverse drug events (ADEs) are grossly under-reported in electronic health records (EHRs). This could be mitigated by methods that are able to detect ADEs in EHRs, thereby allowing for missing ADE-specific diagnosis codes to be identified and added. A crucial aspect of constructing such systems is to find proper representations of the data in order to allow the predictive modeling to be as accurate as possible. One category of EHR data that can be used as indicators of ADEs are clinical measurements. However, using clinical measurements as features is not unproblematic due to the high rate of missing values and they can be repeated a variable number of times in each patient health record. In this study, five basic representations of clinical measurements are proposed and evaluated to handle these two problems. An empirical investigation using random forest on 27 datasets from a real EHR database with different ADE targets is presented, demonstrating that the predictive performance, in terms of accuracy and area under ROC curve, is higher when representing clinical measurements crudely as whether they were taken or how many times they were taken by a patient. Furthermore, a sixth alternative, combining all five basic representations, significantly outperforms using any of the basic representation except for one. A subsequent analysis of variable importance is also conducted with this fused feature set, showing that when clinical measurements have a high missing rate, the number of times they were taken by one patient is ranked as more informative than looking at their actual values. The observation from random forest is also confirmed empirically using other commonly employed classifiers. This study demonstrates that the way in which clinical measurements from EHRs are presented has a high impact for ADE detection, and that using multiple representations outperforms using a basic representation.

  • 2708.
    Zhao, Jing
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Henriksson, Aron
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Asker, Lars
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Boström, Henrik
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Predictive modeling of structured electronic health records for adverse drug event detection2015In: BMC Medical Informatics and Decision Making, ISSN 1472-6947, E-ISSN 1472-6947, Vol. 15, no SIArticle in journal (Refereed)
    Abstract [en]

    Background: The digitization of healthcare data, resulting from the increasingly widespread adoption of electronic health records, has greatly facilitated its analysis by computational methods and thereby enabled large-scale secondary use thereof. This can be exploited to support public health activities such as pharmacovigilance, wherein the safety of drugs is monitored to inform regulatory decisions about sustained use. To that end, electronic health records have emerged as a potentially valuable data source, providing access to longitudinal observations of patient treatment and drug use. A nascent line of research concerns predictive modeling of healthcare data for the automatic detection of adverse drug events, which presents its own set of challenges: it is not yet clear how to represent the heterogeneous data types in a manner conducive to learning high-performing machine learning models. Methods: Datasets from an electronic health record database are used for learning predictive models with the purpose of detecting adverse drug events. The use and representation of two data types, as well as their combination, are studied: clinical codes, describing prescribed drugs and assigned diagnoses, and measurements. Feature selection is conducted on the various types of data to reduce dimensionality and sparsity, while allowing for an in-depth feature analysis of the usefulness of each data type and representation. Results: Within each data type, combining multiple representations yields better predictive performance compared to using any single representation. The use of clinical codes for adverse drug event detection significantly outperforms the use of measurements; however, there is no significant difference over datasets between using only clinical codes and their combination with measurements. For certain adverse drug events, the combination does, however, outperform using only clinical codes. Feature selection leads to increased predictive performance for both data types, in isolation and combined. Conclusions: We have demonstrated how machine learning can be applied to electronic health records for the purpose of detecting adverse drug events and proposed solutions to some of the challenges this presents, including how to represent the various data types. Overall, clinical codes are more useful than measurements and, in specific cases, it is beneficial to combine the two.

  • 2709.
    Zhao, Jing
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Henriksson, Aron
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Boström, Henrik
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Cascading Adverse Drug Event Detection in Electronic Health Records2015In: 2015 IEEE International Conference on Data Science and Advanced Analytics (DSAA): Proceedings, IEEE Computer Society, 2015Conference paper (Refereed)
    Abstract [en]

    The ability to detect adverse drug events (ADEs) in electronic health records (EHRs) is useful in many medical applications, such as alerting systems that indicate when an ADE-specific diagnosis code should be assigned. Automating the detection of ADEs can be attempted by applying machine learning to existing, labeled EHR data. How to do this in an effective manner is, however, an open question. The issues addressed in this study concern the granularity of the classification task: (1) If we wish to predict the occurrence of ADE, is it advantageous to conflate the various ADE class labels prior to learning, or should they be merged post prediction? (2) If we wish to predict a family of ADEs or even a specific ADE, can the predictive performance be enhanced by dividing the classification task into a cascading scheme: predicting first, on a coarse level, whether there is an ADE or not, and, in the former case, followed by a more specific prediction on which family the ADE belongs to, and then finally a prediction on the specific ADE within that particular family? In this study, we conduct a series of experiments using a real, clinical dataset comprising healthcare episodes that have been assigned one of eight ADE-related diagnosis codes and a set of randomly extracted episodes that have not been assigned any ADE code. It is shown that, when distinguishing between ADEs and non-ADEs, merging the various ADE labels prior to learning leads to significantly higher predictive performance in terms of accuracy and area under ROC curve. A cascade of random forests is moreover constructed to determine either the family of ADEs or the specific class label; here, the performance is indeed enhanced compared to directly employing a one-step prediction. This study concludes that, if predictive performance is of primary importance, the cascading scheme should be the recommended approach over employing a one-step prediction for detecting ADEs in EHRs.

  • 2710.
    Zhao, Jing
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Henriksson, Aron
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Boström, Henrik
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Detecting Adverse Drug Events Using Concept Hierarchies of Clinical Codes2014In: 2014 IEEE International Conference on Healthcare Informatics: Proceedings, IEEE Computer Society, 2014, p. 285-293Conference paper (Refereed)
    Abstract [en]

    Electronic health records (EHRs) provide a potentially valuable source of information for pharmacovigilance. However, adverse drug events (ADEs), which can be encoded in EHRs with specific diagnosis codes, are heavily under-reported. To provide more accurate estimates for drug safety surveillance, machine learning systems that are able to detect ADEs could be used to identify and suggest missing ADE-specific diagnosis codes. A fundamental consideration when building such systems is how to represent the EHR data to allow for accurate predictive modeling. In this study, two types of clinical code are used to represent drugs and diagnoses: the Anatomical Therapeutic Chemical Classification System (ATC) and the International Statistical Classification of Diseases and Health Problems (ICD). More specifically, it is investigated whether their hierarchical structure can be exploited to improve predictive performance. The use of random forests with feature sets that include only the original, low-level, codes is compared to using random forests with feature sets that contain all levels in the hierarchies. An empirical investigation using thirty datasets with different ADE targets is presented, demonstrating that the predictive performance, in terms of accuracy and area under ROC curve, can be significantly improved by exploiting codes on all levels in the hierarchies, compared to using only the low-level encoding. A further analysis is presented in which two strategies are employed for adding features level-wise according to the concept hierarchies: top-down, starting with the highest abstraction levels, and bottom-up, starting with the most specific encoding. The main finding from this subsequent analysis is that predictive performance can be kept at a high level even without employing the more specific levels in the concept hierarchies.

  • 2711.
    Zhao, Jing
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Henriksson, Aron
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Kvist, Maria
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences. Karolinska Institute, Sweden.
    Asker, Lars
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Boström, Henrik
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Handling Temporality of Clinical Events for Drug Safety Surveillance2015In: AMIA Annual Symposium Proceedings, ISSN 1559-4076, Vol. 2015, p. 1371-1380Article in journal (Refereed)
    Abstract [en]

    Using longitudinal data in electronic health records (EHRs) for post-marketing adverse drug event (ADE) detection allows for monitoring patients throughout their medical history. Machine learning methods have been shown to be efficient and effective in screening health records and detecting ADEs. How best to exploit historical data, as encoded by clinical events in EHRs is, however, not very well understood. In this study, three strategies for handling temporality of clinical events are proposed and evaluated using an EHR database from Stockholm, Sweden. The random forest learning algorithm is applied to predict fourteen ADEs using clinical events collected from different lengths of patient history. The results show that, in general, including longer patient history leads to improved predictive performance, and that assigning weights to events according to time distance from the ADE yields the biggest improvement.

  • 2712.
    Zhao, Jing
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Karlsson, Isak
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Asker, Lars
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Boström, Henrik
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Applying Methods for Signal Detection in Spontaneous Reports to Electronic Patient Records2013In: Proceedings of the  19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Association for Computing Machinery (ACM), 2013Conference paper (Refereed)
    Abstract [en]

    Currently, pharmacovigilance relies mainly on disproportionality analysis of spontaneous reports. However, the analysis of spontaneous reports is concerned with several problems, such as reliability, under-reporting and insucient patient information. Longitudinal healthcare data, such as Electronic Patient Records (EPRs) in which comprehensive information of each patient is covered, is a complementary source of information to detect Adverse Drug Events (ADEs). A wide set of disproportionality methods has been developed for analyzing spontaneous reports to assess the risk of reported events being ADEs. This study aims to investigate the use of such methods for detecting ADEs when analyzing EPRs. The data used in this study was extracted from Stockholm EPR Corpus. Four disproportionality methods (proportional reporting rate, reporting odds ratio, Bayesian condence propagation neural network, and Gamma-Poisson shrinker) were applied in two dierent ways to analyze EPRs: creating pseudo spontaneous reports based on all observed drug-event pairs (event-level analysis) or analyzing distinct patients who experienced a drug-event pair (patient-level analysis). The methods were evaluated in a case study on safety surveillance of Celecoxib. The results showed that, among the top 200 signals, more ADEs were detected by the event-level analysis than by the patient-level analysis. Moreover, the event-level analysis also resulted in a higher mean average precision. The main conclusion of this study is that the way in which the disproportionality analysis is applied, the event-level or patient-level analysis, can have a much higher impact on the performance than which disproportionality method is employed.

  • 2713.
    Zhao, Jing
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Papapetrou, Panagiotis
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Asker, Lars
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Boström, Henrik
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Learning from heterogeneous temporal data from electronic health records2017In: Journal of Biomedical Informatics, ISSN 1532-0464, E-ISSN 1532-0480, Vol. 65, p. 105-119Article in journal (Refereed)
    Abstract [en]

    Electronic health records contain large amounts of longitudinal data that are valuable for biomedical informatics research. The application of machine learning is a promising alternative to manual analysis of such data. However, the complex structure of the data, which includes clinical events that are unevenly distributed over time, poses a challenge for standard learning algorithms. Some approaches to modeling temporal data rely on extracting single values from time series; however, this leads to the loss of potentially valuable sequential information. How to better account for the temporality of clinical data, hence, remains an important research question. In this study, novel representations of temporal data in electronic health records are explored. These representations retain the sequential information, and are directly compatible with standard machine learning algorithms. The explored methods are based on symbolic sequence representations of time series data, which are utilized in a number of different ways. An empirical investigation, using 19 datasets comprising clinical measurements observed over time from a real database of electronic health records, shows that using a distance measure to random subsequences leads to substantial improvements in predictive performance compared to using the original sequences or clustering the sequences. Evidence is moreover provided on the quality of the symbolic sequence representation by comparing it to sequences that are generated using domain knowledge by clinical experts. The proposed method creates representations that better account for the temporality of clinical events, which is often key to prediction tasks in the biomedical domain.

  • 2714.
    Zhou, Tuping
    et al.
    Stockholm University, Faculty of Science, Department of Materials and Environmental Chemistry (MMK).
    Shu, Nanjiang
    Stockholm University, Faculty of Science, Department of Materials and Environmental Chemistry (MMK).
    Hovmöller, Sven
    Stockholm University, Faculty of Science, Department of Materials and Environmental Chemistry (MMK).
    A Novel Method for Accurate One-dimensional Protein Structure Prediction Based on Fragment Matching2010In: Bioinformatics, ISSN 1367-4803, E-ISSN 1367-4811, Vol. 26, no 4, p. 470-477Article in journal (Refereed)
    Abstract [en]

    Motivation: The precise prediction of one-dimensional (1D) protein structure as represented by the protein secondary structure and 1D string of discrete state of dihedral angles (i.e. Shape Strings) is a prerequisite for the successful prediction of three-dimensional (3D) structure as well as protein-protein interaction. We have developed a novel 1D structure prediction method, called Frag1D, based on a straightforward fragment matching algorithm and demonstrated its success in the prediction of  three sets of 1D structural alphabets, i.e. the classical three-state secondary structure, three-state Shape Strings and eight-state Shape Strings.

    Results: By exploiting the vast protein sequence and protein structure data available, we have brought secondary structure prediction closer to the expected theoretical limit. When tested by a leave-one-out cross validation on a non-redundant set of PDB cutting at 30% sequence identity containing 5860 protein chains, the overall per-residue accuracy for secondary structure prediction, i.e. Q3 is 82.9%. The overall per-residue accuracy for three-state and eight-state Shape Strings are 85.1% and 71.5% respectively. We have also benchmarked our program with the latest version of PSIPRED for secondary structure prediction and our program predicted 0.3% better in Q3 when tested on 2241 chains with the same training set. For Shape Strings, we compared our method with a recently published method with the same dataset and definition as used by that method. Our program predicted at 2.2% better in accuracy for three-state Shape Strings. By quantitatively investigating the effect of data base size on 1D structure prediction we show that the accuracy increases by about 1% with every doubling of the database size.

  • 2715.
    Zikra, Iyad
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Implementing the Unifying Meta-Model for Enterprise Modeling and Model-Driven Development: An Experience Report2012In: The Practice of Enterprise Modeling: 5th IFIP WG 8.1 Working Conference, PoEM 2012. Proceedings / [ed] Kurt Sandkuhl, Ulf Seigerroth, Janis Stirna, Springer, 2012, p. 172-187Conference paper (Refereed)
    Abstract [en]

    Model-Driven Development (MDD) is becoming increasingly popular as a choice for developing information systems. Tools that support the principles of MDD are also growing in number and variety of available functionality. MetaEdit+ is a meta-modeling tool used for developing Domain Specific Languages and is identified as an MDD tool. The Eclipse Modeling Framework (EMF) and Graphical Modeling Project (GMP) are two Eclipse projects that provide plug-ins to support the principles of MDD. In this paper, we report on our experience in using MetaEdit+ and the Eclipse plug-ins for developing a graphical editor for the unifying meta-model, which is an MDD approach that extends the traditional view of MDD to cover Enterprise Modeling. The two modeling environments are reviewed using functionality areas that are identified by the research community as necessary in MDD tools. This report will provide useful insights for researchers and practitioners alike concerning the use of MetaEdit+ and the Eclipse plug-ins as MDD tools.

  • 2716.
    Zikra, Iyad
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Model-based Requirements for Integrating Cloud Services2016In: Proceedings of the CAiSE'16 Forum, at the 28th International Conference on Advanced Information Systems Engineering (CAiSE 2016) / [ed] Sergio España, Mirjana Ivanović, Miloš Savić, 2016, p. 65-72Conference paper (Refereed)
    Abstract [en]

    Cloud-based services provide an alternative to the in-house implementation of various types of functionality. Organizations rely on such services to minimize the need for long-term commitments and enhance scalability and ubiquitous access to the services. However, achieving complex tasks that require a combination of services is not well studied, despite the potential added value. This paper investigates the requirements encountered when integrating cloud-based services in the modern organization. The paper proposes a model-driven solution for capturing the requirements for integrating cloud-based services. The model is to be used within the larger context of the organizational design; modeling components used to describe requirements are related to other views of the organization. A prototype tool and an example business case are presented to illustrate how the requirements model can be elicited and designed. The models are capable of being transformed into an integration solution.

  • 2717.
    Zikra, Iyad
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    The Communicative Nature of Information Systems Integration as an Enabler for Business IT Alignment2017In: Business Information Systems Workshops: BIS 2016 International Workshops, Leipzig, Germany, July 6-8, 2016, Revised Papers / [ed] Witold Abramowicz, Rainer Alt, Bogdan Franczyk, Springer, 2017, p. 136-147Conference paper (Refereed)
    Abstract [en]

    Patterns of systems integration strive to accommodate the diversity of business ecosystems, including novel Web- and cloud-based services. In this paper, we apply the principles of the language/action paradigm (LAP) to develop a decentralized integration pattern that supports dynamic integration of services. A model is proposed for designing the interacting systems as active and independent entities that seek to communicate with each other. Two modes are enabled in the communication model: an indirect mode, where systems interact via business processes; and a direct mode, where systems directly interface with each other, following four categories. The communication perspective of the proposed integration pattern contributes to realizing the vision of a marketplace for cloud services. It supports a more flexible alternative to centralized integra-tion patterns. The communication model builds on the improved alignment be-tween system design models and the overall organizational design offered by the unifying meta-model for enterprise modeling.

  • 2718.
    Zikra, Iyad
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    España, Sergio
    Ruiz, Marcela
    Pastor, Oscar
    Stirna, Janis
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Aligning Communication Analysis with the Unifying Meta-Model for Enterprise Modeling2012Conference paper (Refereed)
    Abstract [en]

    Enterprise Modeling (EM) captures and represents organizational know-ledge in models that cover different views of the enterprise. The models can be leveraged in the development of information systems. Investigating how to use them as input to Model-Driven Development (MDD) is an open challenge. This paper explores how a holistic EM approach, represented by a unifying meta-model, can benefit from integrating with Communication Analysis, a communication-oriented business process modeling and requirements engineering method. As a first step towards an integrated EM-enabled MDD approach, the unifying meta-model and Communication Analysis meta-model are aligned. A set of guidelines for trans-forming models conforming to the unifying meta-model to Communication Analysis models are formulated. The approach is illustrated using of a lab demo.

  • 2719.
    Zikra, Iyad
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Stirna, Janis
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Zdravkovic, Jelena
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    A Quality-Driven Methodology for Information Systems Integration2017In: Complex Systems Informatics and Modeling Quarterly, E-ISSN 2255-9922, no 12, p. 39-65Article in journal (Refereed)
    Abstract [en]

    Information systems integration is an essential instrument for organizations to attain advantage in today’s growing and fast changing business and technology landscapes. Integration solutions generate added value by combining the functionality and services of heterogeneous and diverse systems. Existing integration environments tend to rely heavily on technical, platform-dependent skills. Consequently, the solutions that they enable are not optimally aligned with the envisioned business goals of the organization. Furthermore, the gap between the goals and the solutions complicates the task of evaluating the quality of integration solutions. To address these challenges, we propose a quality-driven, model-driven methodology for designing and developing integration solutions. The methodology spans organizational and systems design details, providing a holistic view of the integration solution and its underlying business goals. A multi-view meta-model provides the basis for the integration design. Quality factors that affect various aspects of the integration solution guide and inform the progress of the methodology. An example business case is presented to demonstrate the application of the methodology.

  • 2720.
    Zikra, Iyad
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Stirna, Janis
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Zdravkovic, Jelena
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Analyzing the Integration between Requirements and Models in Model Driven Development2011Conference paper (Refereed)
    Abstract [en]

    In Model Driven Development (MDD), models replace software code as the development artifact. At the same time, requirements represent the information that is elaborated in models. However, despite the tight relationship between models and requirements, only a few MDD approaches provide the necessary methodological guidelines and tool support to explicitly facilitate this relationship. In this paper, we analyze existing approaches for integrating requirements with models within MDD. Based on the analysis, we elicit a set of general properties that need to be fulfilled when considering the integration of requirements and models, and we assess the contribution of the considered approaches accordingly.

  • 2721.
    Zikra, Iyad
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Stirna, Janis
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Zdravkovic, Jelena
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Bringing Enterprise Modeling Closer to Model-Driven Development2011In: The Practice of Enterprise Modeling, Springer Berlin Heidelberg , 2011Conference paper (Refereed)
    Abstract [en]

    Enterprise Modeling (EM) provides the means for using models to represent organizational knowledge from different perspectives. When information systems (IS) are involved, Model-Driven Development (MDD) is an approach that focuses on the use of models as primary development artifacts. By observing that EM provides the context for high level requirements, which in turn are the input to MDD, we propose a meta-model that integrates enterprise models and requirements with design models in MDD. The meta-model defines six models that cover both organizational and IS development knowledge. Inter-model relationships ensure an integrated view of the enterprise and the supporting IS by allowing model components to be used across different models. The integrated meta-model is demonstrated through an example case study.

  • 2722.
    Zikra, Iyad
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Stirna, Janis
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Zdravkovic, Jelena
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Identifying Quality Factors of Information Systems Integration Design2017In: Perspectives in Business Informatics Research: 16th International Conference, BIR 2017, Copenhagen, Denmark, August 28–30, 2017, Proceedings / [ed] Björn Johansson, Charles Møller, Atanu Chaudhuri, Frantisek Sudzina, Springer, 2017, p. 45-60Conference paper (Refereed)
    Abstract [en]

    The Information Systems (IS) community has long recognized the importance of studying quality at various stages of the IS design process. Many studies target the quality factors at various stages of design and development. However, research about the factors that specifically affect the quality of IS integration remains largely fragmented. Existing quality frameworks fail to cover integration-specific factors. This motivates the need for a holistic model of integration quality. The paper proposes two artefacts to address this need. It explores the literature of related domains, including systems, model, and process quality to elicit the quality factors that are relevant in the context of IS integration. The factors can be used to evaluate the quality of integration solutions during design and development. The paper also proposes a quality model to describe the quality of the design components of integration solutions following the principles of model-driven development. The model enables the quality factors to be associated with other parts of the IS integration design. The proposed factors are evaluated with the help of expert feedback using a questionnaire, and the quality model is demonstrated with an example business case.

  • 2723.
    Ziyarazavi, Merat
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Magnusson, Christer
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    From Theory to Practice - When and How to Implement Service Value Agreement2013In: Journal of Service Science and Management, ISSN 1940-9893, E-ISSN 1940-9907, Vol. 6, p. 127-142Article in journal (Refereed)
    Abstract [en]

    Traditionally, a Service Level Agreement (SLA) is used as an appendix in IT Service Management agreements to set expectations and delineate the service delivery description as well as the terms and conditions of delivery. However, SLAs are unable to imply and guarantee the added values expected by the customer. Service Value Agreement (SVA) is a newly developed framework that identifies the deliverable added values along with metrics to measure the quality and quantity of achievements in terms of business added values. The objective of this study is to expand the concept of SVA for Application Management (AM) services and suggest guidelines for its implementation in real business cases. This goal is fulfilled through the case study approach and outsourcing industry contributions. Authors suggest discussing the concept of SVA from early stages of the sales lifecycle and implementing it gradually during the steady state phase. Combination of Service Value Mapping approach and Piloting method is suggested for SVA proposition as an option with successful practical history.

  • 2724. Ziyarazavi, Merat
    et al.
    Magnusson, Christer
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Tergesten, Torbjörn
    Qualifying and Quantifying IT Services Added Values in Outsourcing Assignments—Service Value Agreement2012In: Journal of Service Science and Management, ISSN 1940-9893, E-ISSN 1940-9907, Vol. 5, no 4, p. 318-330Article in journal (Refereed)
    Abstract [en]

    Traditionally, a Service Level Agreement (SLA) including service level metrics is used as an appendix in IT Service Management agreements to define the terms and conditions of delivery and set expectations. However, SLA neither implies nor guarantees the added values that are expected by the customer. Besides, due to the nature of IT services, there always exists uncertainty about the agreed services due to which the perceived risk for both customer and provider is high. Moreover, the quality and quantity of delivered values are mostly hidden by hazy marketing slogans. In order to guarantee the values of an offered service, the deliverable added values should be characterized properly, quantified by means of measurable metrics, and agreed upon between the two parties. Such comprehensive material, including the deliverable added values along with their measurable metrics, is called Service Value Agreement (SVA). This research proposes a platform for IT service offerings based on added values by identifying, as well as quantifying, an organization’s objectives in purchasing Application Management (AM) services from a provider firm.

  • 2725.
    Zoric, Goranka
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Engström, Arvid
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Barkhuus, Louise
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Hidalgo, Javier Ruiz
    Kochale, Axel
    Gesture Interaction with Rich TV Content in the Social Setting2014In: Proceedings of TVUX-2013: Workshop on Exploring and Enhancing the User Experience for TV at ACM CHI 2013, 27 April 2013, Paris, France, Association for Computing Machinery (ACM), 2014Conference paper (Other academic)
    Abstract [en]

    The appearance of new immersive TV content has increased the interactive possibilities presented to the viewers. Increased interactivity is seen as a valuable feature in viewing richer television content, but new functionalities are limited by what can be done naturally and intuitively using available devices like remote controls. Therefore, new interaction techniques, such as visual gestures control systems, have appeared aiming to enhance the viewers’ viewing experience. In this work we begin uncovering the potential and challenges of gesture interaction with ultra high definition video for people watching TV together. As a first step we have done a study with a group of people interacting with such content using a gesture-based system in the home environment.

  • 2726.
    Åhlfeldt, Rose-Mharie
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Information Security in Distributed Healthcare: Exploring the Needs for Achieving Patient Safety and Patient Privacy2008Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    In healthcare, patient information is a critical factor. The right information at the right time is a necessity in order to provide the best possible care for a patient. Patient information must also be protected from unauthorized access in order to protect patient privacy. It is furthermore common for patients to visit more than one healthcare provider, which implies a need for cross border healthcare and continuity in the patient process.

    This thesis is focused on information security in healthcare when patient information has to be managed and communicated between various healthcare actors and organizations. The work takes a practical approach with a set of investigations from different perspectives and with different professionals involved. Problems and needs have been identified, and a set of guidelines and recommendations has been suggested and developed in order to improve patient safety as well as patient privacy.

    The results show that a comprehensive view of the entire area concerning patient information management between different healthcare actors is missing. Healthcare, as well as patient processes, have to be analyzed in order to gather knowledge needed for secure patient information management.

    Furthermore, the results clearly show that there are deficiencies both at the technical and the administrative level of security in all investigated healthcare organizations.

    The main contribution areas are: an increased understanding of information security by elaborating on the administrative part of information security, the identification of information security problems and needs in cross border healthcare, and a set of guidelines and recommendations in order to advance information security measures in healthcare.

  • 2727.
    Åkerblom, Beatrice
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Wrigstad, Tobias
    Measuring Polymorphism in Python Programs2016In: SIGPLAN notices, ISSN 0362-1340, E-ISSN 1558-1160, Vol. 51, no 2, p. 114-128Article in journal (Refereed)
    Abstract [en]

    Following the increased popularity of dynamic languages and their increased use in critical software, there have been many proposals to retrofit static type system to these languages to improve possibilities to catch bugs and improve performance. A key question for any type system is whether the types should be structural, for more expressiveness, or nominal, to carry more meaning for the programmer. For retrofitted type systems, it seems the current trend is using structural types. This paper attempts to answer the question to what extent this extra expressiveness is needed, and how the possible polymorphism in dynamic code is used in practise. We study polymorphism in 36 real-world open source Python programs and approximate to what extent nominal and structural types could be used to type these programs. The study is based on collecting traces from multiple runs of the programs and analysing the polymorphic degrees of targets at more than 7 million call-sites. Our results show that while polymorphism is used in all programs, the programs are to a great extent monomorphic. The polymorphism found is evenly distributed across libraries and program-specific code and occur both during program start-up and normal execution. Most programs contain a few megamorphic call-sites where receiver types vary widely. The non-monomorphic parts of the programs can to some extent be typed with nominal or structural types, but none of the approaches can type entire programs.

  • 2728.
    Åkerblom, Beatrice
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Wrigstad, Tobias
    Mattias, Tumlin
    Jonathan, Stendahl
    Tracing dynamic features in python program2014In: Proceedings of the 11th Working Conference on Mining Software Repositories, New York: ACM Press, 2014, p. 292-295Conference paper (Refereed)
    Abstract [en]

    Recent years have seen a number of proposals for adding (retrofitting) static typing to dynamic programming languages, a natural consequence of their growing popularity for non-toy applications across a multitude of domains. These proposals often make assumptions about how programmers write code, and in many cases restrict the way the languages can be used. In the context of Python, this paper describes early results from trace-based collection of run-time data about the use of built-in language features which are inherently hard to type, such as dynamic code generation. The end goal of this work is to facilitate static validation tooling for Python, in particular retrofitting of type systems.

  • 2729.
    Åkerfeldt, Anna
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Education.
    Karlström, Petter
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Selander, Staffan
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Ekenberg, Love
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Lärande i en digital miljö. Observation av 1:12013Report (Other academic)
    Abstract [sv]

    Stockholms universitet fick 2009 i uppdrag av Nacka kommun, Förskola, Fritids & Skola att följa kommunens satsning på att sponsra kommunens skolor med bärbara datorer. En projektgrupp tillsattes och under 2009-2011 har gruppen genomfört olika datainsamlingar i Nacka kommuns skolor för att följa 1:1-satsningen (en dator per elev och lärare). I följande rapport kommer projektet att slutrapporteras. Vi kommer att presentera resultat från fyra delstudier; 1) videoobservationer från klassrumsmiljö, 2) fokusgruppssamtal med lärare och rektorer, 3) enkätundersökning med eleverna samt 4) system- och programanalys.

  • 2730.
    Åkerlund, Kent
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Wettergren, Gunnar
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Student motivation in distance learning environments – what can we do as teachers to support it?2013In: 25th ICDE World Conference (16-18 September 2013, Tianjin, China): [Proceedings], 2013Conference paper (Refereed)
    Abstract [en]

    Much has been said and written about learner satisfaction and how to motivate students in distance learning environments. Sun et al., (2008) proposes the instructor attitude toward e-learning as one significant factor for driving successful e-learning. Gilly Salmon (2003)states that it is of most importance to build communities in the educational platform and to design courses for interaction, participation and feedback. The need for Teacher–student interaction from a pedagogical point of view is undisputed, however focus in this discussion has often been on courses in a context where the three freedoms of distance learning (Freedom of time, place and pace) is some what limited to only include freedom of time and place. Free pace is often limited to fit the teachers and the administration of the course. This paper discusses the consequences of adding the third factor, freedom of pace for the student into the equation and applying it on a large course with 1000+ students. How do we treat the need of teacher – student interaction and the ability to build a community in a course of that size with limited resources available? The conclusions drawn in this paper come from teaching courses in project management both on an undergraduate and graduate level. The courses are given at the Department of Computer and Systems Sciences (DSV), Stockholm University and they are reached through the use of teacher discussions, self-introspective and practical experiences working as a teacher. In a course where students are allowed to study at their own pace (the third variable in the equation) it is almost impossible to create a personal relationship with individual students in the course. This in essence means that we as teachers and course creators must focus our attention on other task such as creating structure for students, making the course clear and easy to use, which is one of the biggest influences on motivation (Wettergren, 2011). The importance of quickness in reacting to student needs and questions is of utmost importance and enough resources should be devoted to this. In giving the courses at DSV we noticed a significant increase in student performance when imposing an 8-hour maximum response time from teachers. Students are studying when it fits their schedules making the timing of help and support when they are stuck even more important. The possibility to ask questions in public forums with quick responses from skilled tutors who facilitate the students to advance in the course created a sense of community. The presence of the teachers affects not only the students who asks the questions, but also the “lurkers” who get the information they need from reading other students questions. The implementation of scaffolding or “fictive” goals is an effective way of improving student motivation, giving them something to strive for (Wettergren, 2011). After implementing grading windows once a month, meaning that teachers only graded assignments and examination once a month we saw an increase in course throughput and student motivation. An added bonus of this implementation was that in doing so we created a more motivating and interesting teacher situation since we could focus on teaching and helping the students more since grading was concentrated to certain parts of the month.

  • 2731. Çelaj, Ilir
    et al.
    Rusu, Lazar
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    IT outsourcing relationships in Swedish public organizations2014In: Perspectives in Business Informatics Research: Proceedings, Springer, 2014, p. 15-29Conference paper (Refereed)
    Abstract [en]

    Information technology (IT) is not only beneficial for the private sector but has a lot to offer for the public sector as well. However, most of the studies in IT outsourcing relationships consider only the private sector and do not pay attention to the public sector. In this context, the research has looked to determine the influential factors in IT outsourcing relationships in Swedish public organizations like are Swedish municipalities and classified them according to the importance. The research methodology used has included a survey among IT outsourcing decision makers from Swedish municipalities and a case study in a Swedish municipality. The survey has revealed that trust, cooperation, commitment, communication, and flexibility are the top five most important factors which are influencing the provider-recipient IT outsourcing relationship in Swedish municipalities. While the case study has revealed that all the factors that were identified during the literature review are influencing the provider-recipient IT outsourcing relationship in Swedish municipalities plus the identification of two new factors which are legislation and economy/money.

  • 2732.
    Östling, Robert
    Stockholm University, Faculty of Humanities, Department of Linguistics, Computational Linguistics.
    A Construction Grammar Method for Disambiguating Swedish Compounds2010In: SLTC 2010 Workshop on Compounds and Multiword Expressions, 2010Conference paper (Refereed)
    Abstract [en]

    This study discusses the structure of Swedish compounds within the framework of Construction Grammar, and applies the result to Word Sense Disambiguation of compound components. A construction-based approach is shown to achieve significantly better results than a set of baselines.

  • 2733.
    Östling, Robert
    Stockholm University, Faculty of Humanities, Department of Linguistics.
    Bayesian Models for Multilingual Word Alignment2015Doctoral thesis, monograph (Other academic)
    Abstract [en]

    In this thesis I explore Bayesian models for word alignment, how they can be improved through joint annotation transfer, and how they can be extended to parallel texts in more than two languages. In addition to these general methodological developments, I apply the algorithms to problems from sign language research and linguistic typology.

    In the first part of the thesis, I show how Bayesian alignment models estimated with Gibbs sampling are more accurate than previous methods for a range of different languages, particularly for languages with few digital resources available—which is unfortunately the state of the vast majority of languages today. Furthermore, I explore how different variations to the models and learning algorithms affect alignment accuracy.

    Then, I show how part-of-speech annotation transfer can be performed jointly with word alignment to improve word alignment accuracy. I apply these models to help annotate the Swedish Sign Language Corpus (SSLC) with part-of-speech tags, and to investigate patterns of polysemy across the languages of the world.

    Finally, I present a model for multilingual word alignment which learns an intermediate representation of the text. This model is then used with a massively parallel corpus containing translations of the New Testament, to explore word order features in 1001 languages.

  • 2734.
    Östling, Robert
    Stockholm University, Faculty of Humanities, Department of Linguistics, Computational Linguistics.
    Bayesian Word Alignment for Massively Parallel Texts2014In: Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics, volume 2: Short Papers, Association for Computational Linguistics, 2014, p. 123-127Conference paper (Refereed)
    Abstract [en]

    There has been a great amount of work done in the field of bitext alignment, but the problem of aligning words in massively parallel texts with hundreds or thousands of languages is largely unexplored. While the basic task is similar, there are also important differences in purpose, method and evaluation between the problems. In this work, I present a non-parametric Bayesian model that can be used for simultaneous word alignment in massively parallel corpora. This method is evaluated on a corpus containing 1144 translations of the New Testament.

  • 2735.
    Östling, Robert
    Stockholm University, Faculty of Humanities, Department of Linguistics, Computational Linguistics.
    Stagger: A modern POS tagger for Swedish2012In: / [ed] Pierre Nugues, 2012Conference paper (Refereed)
  • 2736.
    Östling, Robert
    Stockholm University, Faculty of Humanities, Department of Linguistics, Computational Linguistics.
    Stagger: an Open-Source Part of Speech Tagger for Swedish2013In: Northern European Journal of Language Technology (NEJLT), ISSN 2000-1533, Vol. 3, p. 1-18Article in journal (Refereed)
    Abstract [en]

    This work presents Stagger, a new open-source part of speech tagger for Swedish based on the Averaged Perceptron. By using the SALDO morphological lexicon and semi-supervised learning in the form of Collobert and Weston embeddings, it reaches an accuracy of 96.4% on the standard Stockholm-Umeå Corpus dataset, making it the best single part of speech tagging system reported for Swedish. Accuracy increases to 96.6% on the latest version of the corpus, where the annotation has been revised to increase consistency. Stagger is also evaluated on a new corpus of Swedish blog posts, investigating its out-of-domain performance.

  • 2737.
    Östling, Robert
    Stockholm University, Faculty of Humanities, Department of Linguistics, Computational Linguistics.
    Svenska dialektkartor på sekunden2015In: Språkbruk, ISSN 0358-9293, Vol. 3, p. 10-13Article in journal (Other (popular science, discussion, etc.))
  • 2738.
    Östling, Robert
    Stockholm University, Faculty of Humanities, Department of Linguistics, Computational Linguistics.
    Word order typology through multilingual word alignment2015In: The 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing: Proceedings of the Conference, Volume 2: Short Papers, 2015, p. 205-211Conference paper (Refereed)
    Abstract [en]

    With massively parallel corpora of hundreds or thousands of translations of the same text, it is possible to automatically perform typological studies of language structure using very large language samples. We investigate the domain of wordorder using multilingual word alignment and high-precision annotation transfer in a corpus with 1144 translations in 986 languages of the New Testament. Results are encouraging, with 86% to 96% agreementbetween our method and the manually created WALS database for a range of different word order features. Beyond reproducing the categorical data in WALS and extending it to hundreds of other languages, we also provide quantitative data for therelative frequencies of different word orders, and show the usefulness of this for language comparison. Our method has applications for basic research in linguistic typology, as well as for NLP tasks like transfer learning for dependency parsing, which has been shown to benefit from word order information.

  • 2739.
    Östling, Robert
    et al.
    Stockholm University, Faculty of Humanities, Department of Linguistics, Computational Linguistics.
    Börstell, Carl
    Stockholm University, Faculty of Humanities, Department of Linguistics, General Linguistics.
    Wallin, Lars
    Stockholm University, Faculty of Humanities, Department of Linguistics, Sign Language.
    Enriching the Swedish Sign Language Corpus with Part of Speech Tags Using Joint Bayesian Word Alignment and Annotation Transfer2015In: Proceedings of the 20th Nordic Conference of Computational Linguistics: NODALIDA 2015, May 11-13, 2015, Vilnius, Lithuania / [ed] Beáta Megyesi, Linköping University Electronic Press, 2015, p. 263-268Conference paper (Refereed)
    Abstract [en]

    We have used a novel Bayesian model of joint word alignment and part of speech (PoS) annotation transfer to enrich the Swedish Sign Language Corpus with PoS tags. The annotations were then hand-corrected in order to both improve annotation quality for the corpus, and allow the empirical evaluation presented herein.

  • 2740.
    Östling, Robert
    et al.
    Stockholm University, Faculty of Humanities, Department of Linguistics, Computational Linguistics.
    Grigonyte, Gintare
    Stockholm University, Faculty of Humanities, Department of Linguistics, Computational Linguistics.
    Transparent text quality assessment with convolutional neural networks2017In: Proceedings of the 12th Workshop on Innovative Use of NLP for Building Educational Applications, 2017, p. 282-286Conference paper (Refereed)
    Abstract [en]

    We present a very simple model for text quality assessment based on a deep convolutional neural network, where the only supervision required is one corpus of user-generated text of varying quality, and one contrasting text corpus of consistently high quality. Our model is able to provide local quality assessments in different parts of a text, which allows visual feedback about where potentially problematic parts of the text are located, as well as a way to evaluate which textual features are captured by our model. We evaluate our method on two corpora: a large corpus of manually graded student essays and a longitudinal corpus of language learner written production, and find that the text quality metric learned by our model is a fairly strong predictor of both essay grade and learner proficiency level.

  • 2741.
    Östling, Robert
    et al.
    Stockholm University, Faculty of Humanities, Department of Linguistics, Computational Linguistics.
    Scherrer, Yves
    University of Helsinki.
    Tiedemann, Jörg
    University of Helsinki.
    Tang, Gongbo
    Uppsala University.
    Nieminen, Tommi
    University of Helsinki.
    The Helsinki Neural Machine Translation System2017In: Proceedings of the Second Conference on Machine Translation, Copenhagen, Denmark: Association for Computational Linguistics, 2017, p. 338-347Conference paper (Refereed)
  • 2742.
    Östling, Robert
    et al.
    Stockholm University, Faculty of Humanities, Department of Linguistics, Computational Linguistics.
    Smolentzov, André
    Stockholm University, Faculty of Humanities, Department of Linguistics.
    Tyrefors Hinnerich, Björn
    Stockholm University, Faculty of Social Sciences, Department of Economics.
    Höglin, Erik
    Automated Essay Scoring for Swedish2013In: Proceedings of the Eighth Workshop on Innovative Use of NLP for Building Educational Applications, Association for Computational Linguistics, 2013, p. 42-47Conference paper (Refereed)
    Abstract [en]

    We present the first system developed for automated grading of high school essays written in Swedish. The system uses standard text quality indicators and is able to compare vocabulary and grammar to large reference corpora of blog posts and newspaper articles. The system is evaluated on a corpus of 1 702 essays, each graded independently by the student’s own teacher and also in a blind re-grading process by another teacher. We show that our system’s performance is fair, given the low agreementbetween the two human graders, and furthermore show how it could improve efficiency in a practical setting where one seeks to identify incorrectly graded essays.

  • 2743.
    Östling, Robert
    et al.
    Stockholm University, Faculty of Humanities, Department of Linguistics, Computational Linguistics.
    Tiedemann, Jörg
    Continuous multilinguality with language vectors2017In: Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers, 2017, p. 644-649Conference paper (Refereed)
    Abstract [en]

    Most existing models for multilingual natural language processing (NLP) treat language as a discrete category, and make predictions for either one language or the other. In contrast, we propose using continuous vector representations of language. We show that these can be learned efficiently with a character-based neural language model, and used to improve inference about language varieties not seen during training. In experiments with 1303 Bible translations into 990 different languages, we empirically explore the capacity of multilingual language models, and also show that the language vectors capture genetic relationships between languages.

  • 2744.
    Östling, Robert
    et al.
    Stockholm University, Faculty of Humanities, Department of Linguistics, Computational Linguistics.
    Wirén, Mats
    Stockholm University, Faculty of Humanities, Department of Linguistics, Computational Linguistics.
    Compounding in a Swedish Blog Corpus2013In: Computer mediated discourse across languages / [ed] Laura Álvarez López, Charlotta Seiler Brylla & Philip Shaw, Stockholm: Acta Universitatis Stockholmiensis, 2013, p. 45-63Chapter in book (Refereed)
  • 2745. Östlund, Johan
    et al.
    Wrigstad, Tobias
    Clarke, Dave
    Åkerblom, Beatrice
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Ownership, Uniqueness, Immutability2008In: 46th International Conference on Objects, Models, Components, Patterns (TOOLS-Europe), 2008Conference paper (Refereed)
    Abstract [en]

    Programming in an object-oriented language demands a fine balance between flexibility and control. At one level, objects need to interact freely to achieve our implementation goals. At a higher level, architectural constraints that ensure the system can be understood by new developers and can evolve as requirements change must be met. To resolve this tension, researchers have developed type systems expressing ownership and behavioural restrictions such as immutability. This work reports on our consolidation of the resulting discoveries into a single programming language. Our language, Joe_3, imposes little additional syntactic overhead, yet can encode powerful patterns such as fractional permissions and the reference modes of Flexible Alias Protection.

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