article

Finding aliases on the web using latent semantic analysis

Authors:

Vinay Bhat,

Tim Oates,

Vishal Shanbhag,

Charles NicholasAuthors Info & Claims

Data & Knowledge Engineering, Volume 49, Issue 2

Pages 129 - 143

https://doi.org/10.1016/j.datak.2003.10.006

Published: 01 May 2004 Publication History

Abstract

A common problem faced when gathering information from the web is the use of different names to refer to the same entity. For example, the city in India referred to as Bombay in some documents may be referred to as Mumbai in others because its name officially changed from the former to the latter in 1995. Multiplicity of names can cause relevant documents to be missed by search engines. Our goal is to develop an automated system that discovers additional names for an entity given just one of its names. Latent semantic analysis (LSA) is generally thought to be well-suited for this task [Numerical linear algebra with applications 3(4) (1996) 301]. We demonstrate empirically that under a broad range of circumstances LSA performs poorly, and describe a two-stage algorithm based on LSA that performs significantly better.

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Cited By

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Suwanapong TTheeramunkong TNantajeewarawat E(2010)The vector space models for finding co-occurrence names as aliases in Thai sports newsProceedings of the Second international conference on Intelligent information and database systems: Part I10.5555/1894753.1894769(122-130)Online publication date: 24-Mar-2010
https://dl.acm.org/doi/10.5555/1894753.1894769
Schmitz Pde Graça Pimentel MBulterman DGomes Soares L(2008)The CONCUR framework forcommunity maintenance of curated resourcesProceedings of the eighth ACM symposium on Document engineering10.1145/1410140.1410166(123-126)Online publication date: 16-Sep-2008
https://dl.acm.org/doi/10.1145/1410140.1410166
Chen RLiang JPan R(2008)Using recursive ART network to construction domain ontology based on term frequency and inverse document frequencyExpert Systems with Applications: An International Journal10.1016/j.eswa.2006.09.01934:1(488-501)Online publication date: 1-Jan-2008
https://dl.acm.org/doi/10.1016/j.eswa.2006.09.019
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Index Terms

Finding aliases on the web using latent semantic analysis
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
      1. Language resources
2. Information systems
  1. Information retrieval
  2. Information storage systems

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cover image Data & Knowledge Engineering

Data & Knowledge Engineering Volume 49, Issue 2

Special issue: WIDM 2002

May 2004

94 pages

ISSN:0169-023X

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Elsevier Science Publishers B. V.

Netherlands

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Published: 01 May 2004

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Suwanapong TTheeramunkong TNantajeewarawat E(2010)The vector space models for finding co-occurrence names as aliases in Thai sports newsProceedings of the Second international conference on Intelligent information and database systems: Part I10.5555/1894753.1894769(122-130)Online publication date: 24-Mar-2010
https://dl.acm.org/doi/10.5555/1894753.1894769
Schmitz Pde Graça Pimentel MBulterman DGomes Soares L(2008)The CONCUR framework forcommunity maintenance of curated resourcesProceedings of the eighth ACM symposium on Document engineering10.1145/1410140.1410166(123-126)Online publication date: 16-Sep-2008
https://dl.acm.org/doi/10.1145/1410140.1410166
Chen RLiang JPan R(2008)Using recursive ART network to construction domain ontology based on term frequency and inverse document frequencyExpert Systems with Applications: An International Journal10.1016/j.eswa.2006.09.01934:1(488-501)Online publication date: 1-Jan-2008
https://dl.acm.org/doi/10.1016/j.eswa.2006.09.019
Hu BDasmahapatra SLewis P(2007)Emerging consensus in-situProceedings of the 2nd International Conference on Ontology Matching - Volume 30410.5555/2889662.2889669(72-83)Online publication date: 11-Nov-2007
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Sánchez DMoreno A(2005)Development of new techniques to improve web searchProceedings of the 19th international joint conference on Artificial intelligence10.5555/1642293.1642587(1632-1633)Online publication date: 30-Jul-2005
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Sánchez DMoreno A(2005)Automatic discovery of synonyms and lexicalizations from the WebProceedings of the 2005 conference on Artificial Intelligence Research and Development10.5555/1565835.1565867(205-212)Online publication date: 12-May-2005
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The vector space models for finding co-occurrence names as aliases in Thai sports news

Using latent semantic analysis to find different names for the same entity in free text

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