Analysis of the Wikipedia Category Graph for NLP Applications

In this paper, we discuss two graphs in Wikipedia (i) the article graph, and (ii) the category graph. We perform a graph-theoretic analysis of the category graph, and show that it is a scale-free, small world graph like other well-known lexical semantic networks. We substantiate our findings by transferring semantic relatedness algorithms defined on WordNet to the Wikipedia category graph. To assess the usefulness of the category grap has an NLP resource, we analyze its coverage and the performance of the transferred semantic relatedness algorithms.

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Conference:
HLT-NAACL 2007 / TextGraphs-2: Workshop on Graph-Based Algorithms for Natural Language Processing, 26 April, 2007 Rochester, NY, USA
Date Issued:
2007
URN:
urn:nbn:de:hbz:464-20211028-165817-5
DOI:
10.17185/duepublico/72192
Language:
English
Type of Resource:
Text
Collection:
E-Publications
Subject categories of the Deutsche Nationalbibliografie:
004 Data processing Computer sciences
URL:
https://aclanthology.org/W07-0201
Hosting institution:
Faculty of Engineering, Computer Science and Applied Cognitive Science, Computer Science, Language Technology Lab
accrual policy:
Zesch, T., Gurevych, I. (2007) Analysis of the Wikipedia Category Graph for NLP Applications. In: Proceedings of the TextGraphs-2 Workshop on Graph-
Based Algorithms for Natural Language Processing, pp. 1-8. Association for Computational Linguistics. https://aclanthology.org/W07-0201

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