Article

Automatic computation of semantic proximity using taxonomic knowledge

Authors:

Cai-Nicolas Ziegler,

Georg LausenAuthors Info & Claims

CIKM '06: Proceedings of the 15th ACM international conference on Information and knowledge management

Pages 465 - 474

https://doi.org/10.1145/1183614.1183682

Published: 06 November 2006 Publication History

Abstract

Taxonomic measures of semantic proximity allow us to compute the relatedness of two concepts. These metrics are versatile instruments required for diverse applications, e.g., the Semantic Web, linguistics, and also text mining. However, most approaches are only geared towards hand-crafted taxonomic dictionaries such as WordNet, which only feature a limited fraction of real-world concepts. More specific concepts, and particularly instances of concepts, i.e., names of artists, locations, brand names, etc., are not covered.The contributions of this paper are two fold. First, we introduce a framework based on Google and the Open Directory Project (ODP), enabling us to derive the semantic proximity between arbitrary concepts and instances. Second, we introduce a new taxonomy-driven proximity metric tailored for our framework. Studies with human subjects corroborate our hypothesis that our new metric outperforms benchmark semantic proximity metrics and comes close to human judgement.

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Cited By

Formica ATaglino F(2023)Semantic relatedness in DBpedia: A comparative and experimental assessmentInformation Sciences10.1016/j.ins.2022.11.025621(474-505)Online publication date: Apr-2023
https://doi.org/10.1016/j.ins.2022.11.025
dos Santos ALeal J(2023)A Game with a Purpose for Building Crowdsourced Semantic Relations Datasets for Named EntitiesIntelligent Computing10.1007/978-3-031-37963-5_30(422-439)Online publication date: 20-Aug-2023
https://doi.org/10.1007/978-3-031-37963-5_30
Hadj Taieb MZesch TBen Aouicha M(2019)A survey of semantic relatedness evaluation datasets and proceduresArtificial Intelligence Review10.1007/s10462-019-09796-3Online publication date: 23-Dec-2019
https://doi.org/10.1007/s10462-019-09796-3
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Index Terms

Automatic computation of semantic proximity using taxonomic knowledge
1. Computing methodologies
  1. Machine learning
    1. Learning settings
2. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
      1. Document filtering
      2. Information extraction

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cover image ACM Conferences

CIKM '06: Proceedings of the 15th ACM international conference on Information and knowledge management

November 2006

916 pages

ISBN:1595934332

DOI:10.1145/1183614

General Chair:
Philip S. Yu
IBM T.J. Watson Research Center (USA)
,
Program Chairs:
Vassilis Tsotras
University of California-Riverside (USA)
,
Edward Fox
Virginia Tech (USA)
,
Bing Liu
University of Illinois at Chicago (USA)

Copyright © 2006 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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Published: 06 November 2006

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November 6 - 11, 2006

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Cited By

Formica ATaglino F(2023)Semantic relatedness in DBpedia: A comparative and experimental assessmentInformation Sciences10.1016/j.ins.2022.11.025621(474-505)Online publication date: Apr-2023
https://doi.org/10.1016/j.ins.2022.11.025
dos Santos ALeal J(2023)A Game with a Purpose for Building Crowdsourced Semantic Relations Datasets for Named EntitiesIntelligent Computing10.1007/978-3-031-37963-5_30(422-439)Online publication date: 20-Aug-2023
https://doi.org/10.1007/978-3-031-37963-5_30
Hadj Taieb MZesch TBen Aouicha M(2019)A survey of semantic relatedness evaluation datasets and proceduresArtificial Intelligence Review10.1007/s10462-019-09796-3Online publication date: 23-Dec-2019
https://doi.org/10.1007/s10462-019-09796-3
Liu HZhou DZhao JGao S(2017)Job to Major (J2M): An Open Source Based Application2017 International Conference on Computer Network, Electronic and Automation (ICCNEA)10.1109/ICCNEA.2017.58(101-107)Online publication date: Sep-2017
https://doi.org/10.1109/ICCNEA.2017.58
Ben Aouicha MHadj Taieb MBen Hamadou A(2016)LWCRNeurocomputing10.1016/j.neucom.2016.08.045216:C(816-843)Online publication date: 5-Dec-2016
https://dl.acm.org/doi/10.1016/j.neucom.2016.08.045
Ben Aouicha MHadj Taieb MEzzeddine M(2016)Derivation of "is a" taxonomy from Wikipedia Category GraphEngineering Applications of Artificial Intelligence10.1016/j.engappai.2016.01.03350:C(265-286)Online publication date: 1-Apr-2016
https://dl.acm.org/doi/10.1016/j.engappai.2016.01.033
Vlacheas PGiaffreda RStavroulaki VKelaidonis DFoteinos VPoulios GDemestichas PSomov ABiswas AMoessner K(2013)Enabling smart cities through a cognitive management framework for the internet of thingsIEEE Communications Magazine10.1109/MCOM.2013.652560251:6(102-111)Online publication date: Jun-2013
https://doi.org/10.1109/MCOM.2013.6525602
Chen YWu CGuo XWu J(2012)Semantic Learning Service PersonalizedInternational Journal of Computational Intelligence Systems10.1080/18756891.2012.6705285:1(163-172)Online publication date: Feb-2012
https://doi.org/10.1080/18756891.2012.670528
ZHANG ZGENTILE ACIRAVEGNA F(2012)Recent advances in methods of lexical semantic relatedness – a surveyNatural Language Engineering10.1017/S135132491200012519:04(411-479)Online publication date: 4-May-2012
https://doi.org/10.1017/S1351324912000125
Damljanovic DStankovic MLaublet P(2012)Linked data-based concept recommendationProceedings of the 9th international conference on The Semantic Web: research and applications10.1007/978-3-642-30284-8_9(24-38)Online publication date: 27-May-2012
https://dl.acm.org/doi/10.1007/978-3-642-30284-8_9
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