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Text Retrieval by Term Co-occurrences in a Query-based Vector Space
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
2016 (English)In: Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, 2016, 2356-2365 p.Conference paper, Published paper (Refereed)
Abstract [en]

Term co-occurrence in a sentence or paragraph is a powerful and often overlooked feature for text matching in document retrieval. In our experiments with matching email-style query messages to webpages, such term co-occurrence helped greatly to filter and rank documents, compared to matching document-size bags-of-words. The paper presents the results of the experiments as well as a text-matching model where the query shapes the vector space, a document is modelled by two or three vectors in this vector space, and the query-document similarity score depends on the length of the vectors and the relationships between them.

Place, publisher, year, edition, pages
2016. 2356-2365 p.
National Category
Information Systems
Research subject
Computer and Systems Sciences
Identifiers
URN: urn:nbn:se:su:diva-136602ISBN: 978-4-87974-702-0 (print)OAI: oai:DiVA.org:su-136602DiVA: diva2:1055467
Conference
COLING 2016, the 26th International Conference on Computational Linguistics, Osaka, Japan, December 11-17, 2016
Available from: 2016-12-12 Created: 2016-12-12 Last updated: 2017-08-16Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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Language
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