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EgoSet: Exploiting Word Ego-networks and User-generated Ontology for Multifaceted Set Expansion

Authors:

Eytan AdarAuthors Info & Claims

WSDM '16: Proceedings of the Ninth ACM International Conference on Web Search and Data Mining

Pages 645 - 654

https://doi.org/10.1145/2835776.2835808

Published: 08 February 2016 Publication History

Abstract

A key challenge of entity set expansion is that multifaceted input seeds can lead to significant incoherence in the result set. In this paper, we present a novel solution to handling multifaceted seeds by combining existing user-generated ontologies with a novel word-similarity metric based on skip-grams. By blending the two resources we are able to produce sparse word ego-networks that are centered on the seed terms and are able to capture semantic equivalence among words. We demonstrate that the resulting networks possess internally-coherent clusters, which can be exploited to provide non-overlapping expansions, in order to reflect different semantic classes of the seeds. Empirical evaluation against state-of-the-art baselines shows that our solution, EgoSet, is able to not only capture multiple facets in the input query, but also generate expansions for each facet with higher precision.

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Cited By

Huang SMa SLi YLi YZheng HSerra ESpezzano F(2024)From Retrieval to Generation: Efficient and Effective Entity Set ExpansionProceedings of the 33rd ACM International Conference on Information and Knowledge Management10.1145/3627673.3679837(921-931)Online publication date: 21-Oct-2024
https://dl.acm.org/doi/10.1145/3627673.3679837
Zhang XChen GCui SSheng JLiu TXu HHui Yang GWang HHan SHauff CZuccon GZhang Y(2024)Exogenous and Endogenous Data Augmentation for Low-Resource Complex Named Entity RecognitionProceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3626772.3657754(630-640)Online publication date: 10-Jul-2024
https://dl.acm.org/doi/10.1145/3626772.3657754
Li YHuang SZhang XZhou QLi YLiu RCao YZheng HShen Y(2023)Automatic Context Pattern Generation for Entity Set ExpansionIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2023.327521135:12(12458-12469)Online publication date: 1-Dec-2023
https://doi.org/10.1109/TKDE.2023.3275211
Show More Cited By

Index Terms

EgoSet: Exploiting Word Ego-networks and User-generated Ontology for Multifaceted Set Expansion
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
2. Information systems

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cover image ACM Conferences

WSDM '16: Proceedings of the Ninth ACM International Conference on Web Search and Data Mining

February 2016

746 pages

ISBN:9781450337168

DOI:10.1145/2835776

General Chairs:
Paul N. Bennett
Microsoft Research
,
Vanja Josifovski
Pinterest
,
Program Chairs:
Jennifer Neville
Purdue University
,
Filip Radlinski
Microsoft

Copyright © 2016 ACM.

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Published: 08 February 2016

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WSDM 2016: Ninth ACM International Conference on Web Search and Data Mining

February 22 - 25, 2016

California, San Francisco, USA

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WSDM '16 Paper Acceptance Rate 67 of 368 submissions, 18%;

Overall Acceptance Rate 498 of 2,863 submissions, 17%

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Cited By

Huang SMa SLi YLi YZheng HSerra ESpezzano F(2024)From Retrieval to Generation: Efficient and Effective Entity Set ExpansionProceedings of the 33rd ACM International Conference on Information and Knowledge Management10.1145/3627673.3679837(921-931)Online publication date: 21-Oct-2024
https://dl.acm.org/doi/10.1145/3627673.3679837
Zhang XChen GCui SSheng JLiu TXu HHui Yang GWang HHan SHauff CZuccon GZhang Y(2024)Exogenous and Endogenous Data Augmentation for Low-Resource Complex Named Entity RecognitionProceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3626772.3657754(630-640)Online publication date: 10-Jul-2024
https://dl.acm.org/doi/10.1145/3626772.3657754
Li YHuang SZhang XZhou QLi YLiu RCao YZheng HShen Y(2023)Automatic Context Pattern Generation for Entity Set ExpansionIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2023.327521135:12(12458-12469)Online publication date: 1-Dec-2023
https://doi.org/10.1109/TKDE.2023.3275211
Negreanu CKaraoglu AWilliams JChen SFabian DGordon ALin C(2022)Rows from Many Sources: Enriching row completions from Wikidata with a pre-trained Language ModelCompanion Proceedings of the Web Conference 202210.1145/3487553.3524923(1272-1280)Online publication date: 25-Apr-2022
https://dl.acm.org/doi/10.1145/3487553.3524923
Li YLi YHe YYu TShen YZheng HAmigo ECastells PGonzalo JCarterette BCulpepper JKazai G(2022)Contrastive Learning with Hard Negative Entities for Entity Set ExpansionProceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3477495.3531954(1077-1086)Online publication date: 6-Jul-2022
https://dl.acm.org/doi/10.1145/3477495.3531954
Zhang YZhang YJiang YMichalski MDeng YPopa LZhai CHan J(2022)Entity Set Co-Expansion in StackOverflow2022 IEEE International Conference on Big Data (Big Data)10.1109/BigData55660.2022.10020770(4792-4795)Online publication date: 17-Dec-2022
https://doi.org/10.1109/BigData55660.2022.10020770
Shen JHan JShen JHan J(2022)Taxonomy ConstructionAutomated Taxonomy Discovery and Exploration10.1007/978-3-031-11405-2_3(31-48)Online publication date: 22-Sep-2022
https://doi.org/10.1007/978-3-031-11405-2_3
Shen JHan JShen JHan J(2022)Concept Set ExpansionAutomated Taxonomy Discovery and Exploration10.1007/978-3-031-11405-2_2(9-29)Online publication date: 22-Sep-2022
https://doi.org/10.1007/978-3-031-11405-2_2
Huang ZRahimi RYu PShang JAllan JDiaz FShah CSuel TCastells PJones RSakai T(2021)AutoName: A Corpus-Based Set Naming FrameworkProceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3404835.3463100(2101-2105)Online publication date: 11-Jul-2021
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Zhu WGong HBansal RWeinberg ZChristin NFanti GBhat S(2021)Self-Supervised Euphemism Detection and Identification for Content Moderation2021 IEEE Symposium on Security and Privacy (SP)10.1109/SP40001.2021.00075(229-246)Online publication date: May-2021
https://doi.org/10.1109/SP40001.2021.00075
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