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LINDEN: linking named entities with knowledge base via semantic knowledge

Authors:

Min WangAuthors Info & Claims

WWW '12: Proceedings of the 21st international conference on World Wide Web

Pages 449 - 458

https://doi.org/10.1145/2187836.2187898

Published: 16 April 2012 Publication History

Abstract

Integrating the extracted facts with an existing knowledge base has raised an urgent need to address the problem of entity linking. Specifically, entity linking is the task to link the entity mention in text with the corresponding real world entity in the existing knowledge base. However, this task is challenging due to name ambiguity, textual inconsistency, and lack of world knowledge in the knowledge base. Several methods have been proposed to tackle this problem, but they are largely based on the co-occurrence statistics of terms between the text around the entity mention and the document associated with the entity. In this paper, we propose LINDEN, a novel framework to link named entities in text with a knowledge base unifying Wikipedia and WordNet, by leveraging the rich semantic knowledge embedded in the Wikipedia and the taxonomy of the knowledge base. We extensively evaluate the performance of our proposed LINDEN over two public data sets and empirical results show that LINDEN significantly outperforms the state-of-the-art methods in terms of accuracy.

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Cited By

Cao JFang JMeng ZLiang S(2024)Knowledge Graph Embedding: A Survey from the Perspective of Representation SpacesACM Computing Surveys10.1145/3643806Online publication date: 2-Feb-2024
https://dl.acm.org/doi/10.1145/3643806
Wawrzik FRafique KRahman FGrimm C(2023)Ontology Learning Applications of Knowledge Base Construction for Microelectronic Systems InformationInformation10.3390/info1403017614:3(176)Online publication date: 9-Mar-2023
https://doi.org/10.3390/info14030176
Wei TYang AHuang SSong S(2023)A simple semantic ranking approach for entity linkingThird International Seminar on Artificial Intelligence, Networking, and Information Technology (AINIT 2022)10.1117/12.2667421(43)Online publication date: 22-Feb-2023
https://doi.org/10.1117/12.2667421
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Index Terms

LINDEN: linking named entities with knowledge base via semantic knowledge
1. Information systems
  1. Information retrieval

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Published In

cover image ACM Other conferences

WWW '12: Proceedings of the 21st international conference on World Wide Web

April 2012

1078 pages

ISBN:9781450312295

DOI:10.1145/2187836

General Chairs:
Alain Mille
Université de Lyon, France
,
Fabien Gandon
INRIA, France
,
Jacques Misselis
HP, France
,
Program Chairs:
Michael Rabinovich
Case Western Reserve University, USA
,
Steffen Staab
University of Koblenz-Landau, Germany

Copyright © 2012 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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Univ. de Lyon: Universite de Lyon

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SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 16 April 2012

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WWW 2012

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Univ. de Lyon

WWW 2012: 21st World Wide Web Conference 2012

April 16 - 20, 2012

Lyon, France

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

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Cited By

Cao JFang JMeng ZLiang S(2024)Knowledge Graph Embedding: A Survey from the Perspective of Representation SpacesACM Computing Surveys10.1145/3643806Online publication date: 2-Feb-2024
https://dl.acm.org/doi/10.1145/3643806
Wawrzik FRafique KRahman FGrimm C(2023)Ontology Learning Applications of Knowledge Base Construction for Microelectronic Systems InformationInformation10.3390/info1403017614:3(176)Online publication date: 9-Mar-2023
https://doi.org/10.3390/info14030176
Wei TYang AHuang SSong S(2023)A simple semantic ranking approach for entity linkingThird International Seminar on Artificial Intelligence, Networking, and Information Technology (AINIT 2022)10.1117/12.2667421(43)Online publication date: 22-Feb-2023
https://doi.org/10.1117/12.2667421
Liao XLi YLou YGe XGao SSun P(2023)The SG-CIM Entity Linking Method Based on BERT and Entity Name Embeddings2023 4th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT)10.1109/AINIT59027.2023.10212510(362-366)Online publication date: 16-Jun-2023
https://doi.org/10.1109/AINIT59027.2023.10212510
Ran CShen WGao JLi YWang JJia Y(2022)Learning Entity Linking Features for Emerging EntitiesIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2022.3197707(1-14)Online publication date: 2022
https://doi.org/10.1109/TKDE.2022.3197707
Khan AMalik S(2022)Knowledge Base Entity Lookup using Named Entity Recognition: a case study on YAGO2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)10.1109/ICCCIS56430.2022.10037689(429-434)Online publication date: 4-Nov-2022
https://doi.org/10.1109/ICCCIS56430.2022.10037689
Su JJiang WZhang N(2022)An entity linking method based on graph feature and electricity domain knowledge base2022 International Conference on Computers, Information Processing and Advanced Education (CIPAE)10.1109/CIPAE55637.2022.00065(276-281)Online publication date: Aug-2022
https://doi.org/10.1109/CIPAE55637.2022.00065
Qi YMa HShi LZan HZhou Q(2022)Adversarial Transfer for Classical Chinese NER with Translation Word SegmentationNatural Language Processing and Chinese Computing10.1007/978-3-031-17120-8_24(298-310)Online publication date: 24-Sep-2022
https://doi.org/10.1007/978-3-031-17120-8_24
Lv QZheng LWang M(2022)Chinese Named Entity Recognition Based on Dynamically Adjusting Feature WeightsCollaborative Computing: Networking, Applications and Worksharing10.1007/978-3-030-92635-9_1(3-19)Online publication date: 1-Jan-2022
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Alsaudi AAltowim YMehrotra SYu Y(2021)TQELProceedings of the VLDB Endowment10.14778/3476249.347630914:11(2642-2654)Online publication date: 27-Oct-2021
https://dl.acm.org/doi/10.14778/3476249.3476309
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