Article in Proceedings INPROC-2009-29

BibliographyKaiser, Fabian; Schwarz, Holger; Jakob, Mihály: Using Wikipedia-based conceptual contexts to calculate document similarity.
In: ICDS2009: Proceedings of the 3rd International Conference on Digital Society.
University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology.
pp. 322-327, english.
Cancun, Mexico: IEEE Computer Society, February 2009.
Article in Proceedings (Conference Paper).
CR-SchemaH.3 (Information Storage and Retrieval)
H.3.3 (Information Search and Retrieval)
Abstract

Rating the similarity of two or more text documents is an essential task in information retrieval. For example, document similarity can be used to rank search engine results, cluster documents according to topics etc. A major challenge in calculating document similarity originates from the fact that two documents can have the same topic or even mean the same, while they use different wording to describe the content. A sophisticated algorithm therefore will not directly operate on the texts but will have to find a more abstract representation that captures the texts' meaning. In this paper, we propose a novel approach for calculating the similarity of text documents. It builds on conceptual contexts that are derived from content and structure of the Wikipedia hypertext corpus.

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Department(s)University of Stuttgart, Institute of Parallel and Distributed Systems, Applications of Parallel and Distributed Systems
Entry dateMarch 9, 2009
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