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SEISA: set expansion by iterative similarity aggregation

Authors:

Dong XinAuthors Info & Claims

WWW '11: Proceedings of the 20th international conference on World wide web

Pages 427 - 436

https://doi.org/10.1145/1963405.1963467

Published: 28 March 2011 Publication History

Abstract

In this paper, we study the problem of expanding a set of given seed entities into a more complete set by discovering other entities that also belong to the same concept set. A typical example is to use "Canon" and "Nikon" as seed entities, and derive other entities (e.g., "Olympus") in the same concept set of camera brands. In order to discover such relevant entities, we exploit several web data sources, including lists extracted from web pages and user queries from a web search engine. While these web data are highly diverse with rich information that usually cover a wide range of the domains of interest, they tend to be very noisy. We observe that previously proposed random walk based approaches do not perform very well on these noisy data sources. Accordingly, we propose a new general framework based on iterative similarity aggregation, and present detailed experimental results to show that, when using general-purpose web data for set expansion, our approach outperforms previous techniques in terms of both precision and recall.

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Cited By

Chaganty ALeszczynski MZhang SGanti RBalog KRadlinski FChen HDuh WHuang HKato MMothe JPoblete B(2023)Beyond Single Items: Exploring User Preferences in Item Sets with the Conversational Playlist Curation DatasetProceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3539618.3591881(2754-2764)Online publication date: 19-Jul-2023
https://dl.acm.org/doi/10.1145/3539618.3591881
Helm HBasu AAthreya APark YVogelstein JPriebe CWinding MZlatic MCardona ABourke PLarson JAbdin MChoudhury PYang WWhite C(2023)Distance-based positive and unlabeled learning for rankingPattern Recognition10.1016/j.patcog.2022.109085134:COnline publication date: 1-Feb-2023
https://dl.acm.org/doi/10.1016/j.patcog.2022.109085
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
Show More Cited By

Index Terms

SEISA: set expansion by iterative similarity aggregation
1. Information systems
  1. Information systems applications
    1. Data mining

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Information & Contributors

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Published In

cover image ACM Other conferences

WWW '11: Proceedings of the 20th international conference on World wide web

March 2011

840 pages

ISBN:9781450306324

DOI:10.1145/1963405

General Chairs:
S. Sadagopan
IIIT-Bangalore, India
,
Krithi Ramamritham
IIT-Bombay, India
,
Arun Kumar
IBM Research, India
,
M. P. Ravindra
Infosys E & R, India
,
Program Chairs:
Elisa Bertino
Purdue University, USA
,
Ravi Kumar
Yahoo! Research, USA

Copyright © 2011 ACM.

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 ACM 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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SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web
The International Institute of Information Technology Bangalore: The International Institute of Information Technology Bangalore

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 28 March 2011

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WWW '11

WWW '11: 20th International World Wide Web Conference

March 28 - April 1, 2011

Hyderabad, India

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Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Cited By

Chaganty ALeszczynski MZhang SGanti RBalog KRadlinski FChen HDuh WHuang HKato MMothe JPoblete B(2023)Beyond Single Items: Exploring User Preferences in Item Sets with the Conversational Playlist Curation DatasetProceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3539618.3591881(2754-2764)Online publication date: 19-Jul-2023
https://dl.acm.org/doi/10.1145/3539618.3591881
Helm HBasu AAthreya APark YVogelstein JPriebe CWinding MZlatic MCardona ABourke PLarson JAbdin MChoudhury PYang WWhite C(2023)Distance-based positive and unlabeled learning for rankingPattern Recognition10.1016/j.patcog.2022.109085134:COnline publication date: 1-Feb-2023
https://dl.acm.org/doi/10.1016/j.patcog.2022.109085
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
Zheng YShi CCao XLi XWu B(2022)A Meta Path Based Method for Entity Set Expansion in Knowledge GraphIEEE Transactions on Big Data10.1109/TBDATA.2018.28053668:3(616-629)Online publication date: 1-Jun-2022
https://doi.org/10.1109/TBDATA.2018.2805366
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
Venktesh VMohania MGoyal V(2022)Topic Aware Contextualized Embeddings for High Quality Phrase ExtractionAdvances in Information Retrieval10.1007/978-3-030-99736-6_31(457-471)Online publication date: 10-Apr-2022
https://dl.acm.org/doi/10.1007/978-3-030-99736-6_31
Wahed MGruhl DAlba AGentile ARistoski PDeLuca CWelch SLourentzou IDemartini GZuccon GCulpepper JHuang ZTong H(2021)SAUCEProceedings of the 30th ACM International Conference on Information & Knowledge Management10.1145/3459637.3481950(4173-4183)Online publication date: 26-Oct-2021
https://dl.acm.org/doi/10.1145/3459637.3481950
Song JHe YLi GLi ZIdreos SSrivastava D(2021)Auto-Validate: Unsupervised Data Validation Using Data-Domain Patterns Inferred from Data LakesProceedings of the 2021 International Conference on Management of Data10.1145/3448016.3457250(1678-1691)Online publication date: 9-Jun-2021
https://dl.acm.org/doi/10.1145/3448016.3457250
Xia SAnzum NSalihoglu SZhao JKitamura YQuigley AIsbister KIgarashi TBjørn PDrucker S(2021)KTabulator: Interactive Ad hoc Table Creation using Knowledge GraphsProceedings of the 2021 CHI Conference on Human Factors in Computing Systems10.1145/3411764.3445227(1-14)Online publication date: 6-May-2021
https://dl.acm.org/doi/10.1145/3411764.3445227
Zhu WGong HShen JZhang CShang JBhat SHan J(2021)FUSE: Multi-faceted Set Expansion by Coherent Clustering of Skip-GramsMachine Learning and Knowledge Discovery in Databases10.1007/978-3-030-67664-3_37(617-632)Online publication date: 25-Feb-2021
https://doi.org/10.1007/978-3-030-67664-3_37
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