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Representing word semantics for IR by continuous functions
University of Borås, Swedish School of Library and Information Science.
University of Borås, Swedish School of Library and Information Science.
2007 (English)In: Studies in Theory of Information Retrieval. Proceedings of the ICTIR07 Conference, Budapest, 18-20 October 2007 / [ed] Sándor Dominich, Ferenc Kiss, Foundation for Information Society, Budapest , 2007, 149-155 p.Conference paper (Refereed)
Abstract [en]

Information representation is an important but neglected aspect of building text information retrieval models. In order to be efficient, the mathematical objects of a formal model, like vectors, have to reasonably reproduce language-related phenomena such as word meaning inherent in index terms. On the other hand, the classical vector space model, when it comes to the representation of word meaning, is approximative only, whereas it exactly localizes term, query and document content. It can be shown that by replacing vectors by continuous functions, information retrieval in Hilbert space yields comparable or better results. This is because according to the non-classical or continuous vector space model, content cannot be exactly localized. At the same time, the model relies on a richer representation of word meaning than the VSM can offer.

Place, publisher, year, edition, pages
Foundation for Information Society, Budapest , 2007. 149-155 p.
Keyword [en]
information retrieval, language representation, word semantics, signal processing, Information retrieval, information representation
National Category
Information Studies Specific Languages Atom and Molecular Physics and Optics Mathematics
URN: urn:nbn:se:hb:diva-5855ISI: 000300454800001Local ID: 2320/3229ISBN: 978-963-06-3237-9OAI: diva2:886537
Available from: 2015-12-22 Created: 2015-12-22

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