Cited By
View all- Saedi AFatemi ANematbakhsh MRosset SVilnat A(2025)Entity search based on consumer preferences leveraging user reviewsExpert Systems with Applications10.1016/j.eswa.2025.126990(126990)Online publication date: Feb-2025
FindiLike: a preference driven entity search engine for evaluating entity retrieval and opinion summarization
Pages 19 - 22
Abstract
We describe a novel preference-driven search engine (FindiLike) which allows users to find entities of interest based on preferences and also allows users to digest opinions about the retrieved entities easily. FindiLike leverages large amounts of online reviews about various entities, and ranks entities based on how well their associated reviews match a user's preference query (expressed in keywords). FindiLike then uses abstractive summarization techniques to generate concise opinion summaries to enable users to digest the opinions about an entity. We discuss how the system can be extended to support in situ evaluation of two interesting new tasks, i.e., opinion-based entity ranking and abstractive summarization of opinions. The system is currently supporting hotel search and being extended to support in situ evaluation of these two tasks. We will demonstrate the system in the domain of hotel search and show how in situ evaluation can be supported through natural user interaction with the system.
References
[1]
K. Ganesan and C. Zhai. Opinion-based entity ranking. Information Retrieval, 2011.
[2]
K. Ganesan and C. Zhai. Findilike: Preference driven entity search. Proceedings of the 21st International Conference on World Wide Web 2012 (WWW 12), Demo, 2012.
[3]
K. Ganesan, C. Zhai, and J. Han. Opinosis: A graph based approach to abstractive summarization of highly redundant opinions. In Proceedings of the 23rd International Conference on Computational Linguistics (COLING), Beijing, China, 2010.
[4]
K. Ganesan, C. Zhai, and E. Viegas. Micropinion generation: An unsupervised approach to generating ultra-concise summaries of opinions. In Proceedings of the 21st International Conference on World Wide Web (WWW 12), 2012.
[5]
T. Joachims. Optimizing search engines using clickthrough data. In Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining, KDD '02, pages 133--142, New York, NY, USA, 2002. ACM.
[6]
T. Joachims et al. Evaluating retrieval performance using clickthrough data.
Index Terms
- FindiLike: a preference driven entity search engine for evaluating entity retrieval and opinion summarization
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Published In
November 2013
34 pages
ISBN:9781450324205
DOI:10.1145/2513150
- General Chairs:
- Krisztian Balog,
- David Elsweiler,
- Evangelos Kanoulas,
- Liadh Kelly,
- Mark Smucker
Copyright © 2013 Owner/Author.
Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 01 November 2013
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CIKM'13: 22nd ACM International Conference on Information and Knowledge Management
November 1, 2013
California, San Francisco, USA
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LivingLab '13 Paper Acceptance Rate 7 of 7 submissions, 100%;
Overall Acceptance Rate 7 of 7 submissions, 100%
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View all- Saedi AFatemi ANematbakhsh MRosset SVilnat A(2025)Entity search based on consumer preferences leveraging user reviewsExpert Systems with Applications10.1016/j.eswa.2025.126990(126990)Online publication date: Feb-2025
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