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A Random Indexing Approach to Unsupervised Selectional Preference Induction
Stockholms universitet, Humanistiska fakulteten, Institutionen för lingvistik, Avdelningen för datorlingvistik. (Datorlingvistik)
Stockholms universitet, Humanistiska fakulteten, Institutionen för lingvistik, Avdelningen för datorlingvistik. (Datorlingvistik)ORCID-id: 0000-0002-4269-5619
2011 (engelsk)Independent thesis Basic level (degree of Bachelor), 10 poäng / 15 hpOppgave
Abstract [en]

A selectional preference is the relation between a head-word and plausible arguments of that head-word. Estimation of the association feature between these words is important to natural language processing applications such as Word Sense Disambiguation. This study presents a novel approach to selectional preference induction within a Random Indexing word space. This is a spatial representation of meaning where distributional patterns enable estimation of the similarity between words. Using only frequency statistics about words to estimate how strongly one word selects another, the aim of this study is to develop a flexible method that is not language dependent and does not require any annotated resourceswhich is in contrast to methods from previous research. In order to optimize the performance of the selectional preference model, experiments including parameter tuning and variation of corpus size were conducted. The selectional preference model was evaluated in a pseudo-word evaluation which lets the selectional preference model decide which of two arguments have a stronger correlation to a given verb. Results show that varying parameters and corpus size does not affect the performance of the selectional preference model in a notable way. The conclusion of the study is that the language modelused does not provide the adequate tools to model selectional preferences. This might be due to a noisy representation of head-words and their arguments.

sted, utgiver, år, opplag, sider
2011. , s. 28
Emneord [en]
Selectional preference induction, selectional preferences, word space model, Random Indexing, syntagma, distributional hypothesis
HSV kategori
Identifikatorer
URN: urn:nbn:se:su:diva-59493OAI: oai:DiVA.org:su-59493DiVA, id: diva2:428507
Presentation
2011-06-01, C307, Institutionen för lingvistik, Universitetsvägen 10 C, Stockholm, 10:00 (svensk)
Uppsök
Humanities, Theology
Veileder
Examiner
Tilgjengelig fra: 2011-07-04 Laget: 2011-06-30 Sist oppdatert: 2018-01-12bibliografisk kontrollert

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