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Timestamping Entities using Contextual Information

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SIGIR '17: Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval

Pages 1205 - 1208

https://doi.org/10.1145/3077136.3080762

Published: 07 August 2017 Publication History

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Abstract

Wikipedia is the result of collaborative effort aiming to represent human knowledge and to make it accessible to the public. Many Wikipedia articles however lack key metadata information. For example, relatively large number of people described in Wikipedia have no information on their birth and death dates. We propose in this paper to estimate entity's lifetimes using link structure in Wikipedia focusing on person entities. Our approach is based on propagating temporal information over links between Wikipedia articles.

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Cited By

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Sumikawa YJatowt A(2020)Analyzing history-related posts in twitterInternational Journal on Digital Libraries10.1007/s00799-020-00296-2Online publication date: 28-Oct-2020
https://doi.org/10.1007/s00799-020-00296-2
Sumikawa YIkejiri R(2020)Feature selection for classifying multi-labeled past eventsInternational Journal on Digital Libraries10.1007/s00799-020-00293-5Online publication date: 8-Sep-2020
https://doi.org/10.1007/s00799-020-00293-5
Jatowt AKawai DTanaka K(2018)Time-focused analysis of connectivity and popularity of historical persons in WikipediaInternational Journal on Digital Libraries10.1007/s00799-018-0231-4Online publication date: 8-Feb-2018
https://doi.org/10.1007/s00799-018-0231-4

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Published In

SIGIR '17: Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval

August 2017

1476 pages

ISBN:9781450350228

DOI:10.1145/3077136

General Chairs:
Noriko Kando
National Institute of Informatics
,
Tetsuya Sakai
Waseda University
,
Hideo Joho
University of Tsukuba
,
Program Chairs:
Hang Li
Huawei Noah's Ark Lab
,
Arjen P. de Vries
Radboud University
,
Ryen W. White
Microsoft Cortana

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 07 August 2017

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Short-paper

Funding Sources

Japan Science and Technology Agency (JST)

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SIGIR '17

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SIGIR

SIGIR '17: The 40th International ACM SIGIR conference on research and development in Information Retrieval

August 7 - 11, 2017

Tokyo, Shinjuku, Japan

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SIGIR '17 Paper Acceptance Rate 78 of 362 submissions, 22%;

Overall Acceptance Rate 792 of 3,983 submissions, 20%

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Cited By

View all

Sumikawa YJatowt A(2020)Analyzing history-related posts in twitterInternational Journal on Digital Libraries10.1007/s00799-020-00296-2Online publication date: 28-Oct-2020
https://doi.org/10.1007/s00799-020-00296-2
Sumikawa YIkejiri R(2020)Feature selection for classifying multi-labeled past eventsInternational Journal on Digital Libraries10.1007/s00799-020-00293-5Online publication date: 8-Sep-2020
https://doi.org/10.1007/s00799-020-00293-5
Jatowt AKawai DTanaka K(2018)Time-focused analysis of connectivity and popularity of historical persons in WikipediaInternational Journal on Digital Libraries10.1007/s00799-018-0231-4Online publication date: 8-Feb-2018
https://doi.org/10.1007/s00799-018-0231-4

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Discovering Missing Semantic Relations between Entities in Wikipedia

Two-stage approach to named entity recognition using Wikipedia and DBpedia

Fast Linking of Mathematical Wikidata Entities in Wikipedia Articles Using Annotation Recommendation