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  1. Proceedings of the 7th Forum for Information Retrieval Evaluation (FIRE '15)
  2. An Empirical Comparison of Statistical Term Association Graphs with DBpedia and ConceptNet for Query Expansion
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An Empirical Comparison of Statistical Term Association Graphs with DBpedia and ConceptNet for Query Expansion

Content Provider ACM Digital Library
Author Kotov, Alexander Anand, Rajul
Abstract Term graphs constructed from document collections as well as external resources, such as encyclopedias (DBpedia) and knowledge bases (ConceptNet), can be used as sources of semantically related terms for query expansion. Although these resources individually have been shown to be effective for IR, it is not known how their retrieval effectiveness compares with each other. In this work, we use standard TREC collections to perform systematic evaluation and empirical comparison of retrieval effectiveness of both types of term graphs for all and difficult queries. Our results indicate that of the term association graphs constructed automatically from document collection using information theoretic measures are more effective for Web collections, while the term graphs derived from DBpedia and ConceptNet are more effective for newswire collections.
Starting Page 27
Ending Page 30
Page Count 4
File Format PDF
ISBN 9781450340045
DOI 10.1145/2838706.2838715
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2015-12-04
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Term graphs Knowledge graphs Query expansion
Content Type Text
Resource Type Article
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