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An Empirical Comparison of Statistical Term Association Graphs with DBpedia and ConceptNet for Query Expansion

Authors:

Rajul Anand,

Alexander KotovAuthors Info & Claims

FIRE '15: Proceedings of the 7th Annual Meeting of the Forum for Information Retrieval Evaluation

Pages 27 - 30

https://doi.org/10.1145/2838706.2838715

Published: 04 December 2015 Publication History

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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.

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Cited By

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Sharma DPamula RChauhan D(2022)A contemporary combined approach for query expansionMultimedia Tools and Applications10.1007/s11042-020-09172-281:24(35195-35221)Online publication date: 1-Oct-2022
https://dl.acm.org/doi/10.1007/s11042-020-09172-2
Shukla ADas S(2021)A Hybrid Model of Query Expansion using Word2Vec2021 IEEE International Conference on Technology, Research, and Innovation for Betterment of Society (TRIBES)10.1109/TRIBES52498.2021.9751673(1-6)Online publication date: 17-Dec-2021
https://doi.org/10.1109/TRIBES52498.2021.9751673
Sharma DPamula RChauhan D(2019)Combined techniques based query expansion approach for document retrieval system2019 International Conference on contemporary Computing and Informatics (IC3I)10.1109/IC3I46837.2019.9055709(101-105)Online publication date: Dec-2019
https://doi.org/10.1109/IC3I46837.2019.9055709
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Index Terms

An Empirical Comparison of Statistical Term Association Graphs with DBpedia and ConceptNet for Query Expansion
1. Information systems
  1. Information retrieval

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Published In

FIRE '15: Proceedings of the 7th Annual Meeting of the Forum for Information Retrieval Evaluation

December 2015

57 pages

ISBN:9781450340045

DOI:10.1145/2838706

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

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Published: 04 December 2015

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FIRE '15

FIRE '15: Forum for Information Retrieval Evaluation

December 4 - 6, 2015

Gandhinagar, India

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FIRE '15 Paper Acceptance Rate 12 of 42 submissions, 29%;

Overall Acceptance Rate 19 of 64 submissions, 30%

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Sharma DPamula RChauhan D(2022)A contemporary combined approach for query expansionMultimedia Tools and Applications10.1007/s11042-020-09172-281:24(35195-35221)Online publication date: 1-Oct-2022
https://dl.acm.org/doi/10.1007/s11042-020-09172-2
Shukla ADas S(2021)A Hybrid Model of Query Expansion using Word2Vec2021 IEEE International Conference on Technology, Research, and Innovation for Betterment of Society (TRIBES)10.1109/TRIBES52498.2021.9751673(1-6)Online publication date: 17-Dec-2021
https://doi.org/10.1109/TRIBES52498.2021.9751673
Sharma DPamula RChauhan D(2019)Combined techniques based query expansion approach for document retrieval system2019 International Conference on contemporary Computing and Informatics (IC3I)10.1109/IC3I46837.2019.9055709(101-105)Online publication date: Dec-2019
https://doi.org/10.1109/IC3I46837.2019.9055709
Raza MMokhtar RAhmad NPasha MPasha U(2019)A Taxonomy and Survey of Semantic Approaches for Query ExpansionIEEE Access10.1109/ACCESS.2019.28946797(17823-17833)Online publication date: 2019
https://doi.org/10.1109/ACCESS.2019.2894679
Khennak IDrias H(2017)An accelerated PSO for query expansion in web information retrievalApplied Intelligence10.1007/s10489-017-0924-147:3(793-808)Online publication date: 1-Oct-2017
https://dl.acm.org/doi/10.1007/s10489-017-0924-1

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Query expansion based on term distribution and DBpedia features

A Term Cluster Query Expansion Model Based on Classification Information in Natural Language Information Retrieval

A query term re-weighting approach using document similarity

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