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  Discovering a Term Taxonomy from Term Similarities Using Principal Component Analysis

Bast, H., Dupret, G., Majumdar, D., & Piwowarski, B. (2006). Discovering a Term Taxonomy from Term Similarities Using Principal Component Analysis. In Semantics, web and mining : Joint International Workshops, EWMF 2005 and KDO 2005 (pp. 103-120). Berlin, Germany: Springer.

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 Creators:
Bast, Holger1, Author           
Dupret, Georges1, Author           
Majumdar, Debapriyo1, Author           
Piwowarski, Benjamin, Author
Ackermann, Markus, Editor
Berendt, Bettina, Editor
Grobelnik, Marko, Editor
Hotho, Andreas, Editor
Mladenic, Dunja, Editor
Semeraro, Giovanni, Editor
Spiliopoulou, Myra, Editor
Stumme, Gerd, Editor
Svatek, Vojtech, Editor
van Someren, Maarten W., Editor
Affiliations:
1Algorithms and Complexity, MPI for Informatics, Max Planck Society, ou_24019              

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 Abstract: We show that eigenvector decomposition can be used to extract a term taxonomy from a given collection of text documents. So far, methods based on eigenvector decomposition, such as latent semantic indexing (LSI) or principal component analysis (PCA), were only known to be useful for extracting symmetric relations between terms. We give a precise mathematical criterion for distinguishing between four kinds of relations of a given pair of terms of a given collection: unrelated (car - fruit), symmetrically related (car - automobile), asymmetrically related with the first term being more specific than the second (banana - fruit), and asymmetrically related in the other direction (fruit - banana). We give theoretical evidence for the soundness of our criterion, by showing that in a simplified mathematical model the criterion does the apparently right thing. We applied our scheme to the reconstruction of a selected part of the open directory project (ODP) hierarchy, with promising results.

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Language(s): eng - English
 Dates: 2007-03-172006
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: eDoc: 314391
Other: Local-ID: C1256428004B93B8-A57781D850A00AD5C12571EA0072C7DF-BastDMP06
 Degree: -

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Title: Untitled Event
Place of Event: Porto, Portugal
Start-/End Date: 2005-10-03

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Source 1

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Title: Semantics, web and mining : Joint International Workshops, EWMF 2005 and KDO 2005
Source Genre: Proceedings
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Publ. Info: Berlin, Germany : Springer
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 103 - 120 Identifier: ISBN: 978-3-540-47697-9

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Title: Lecture Notes in Computer Science
Source Genre: Series
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Pages: - Volume / Issue: 4289 Sequence Number: - Start / End Page: - Identifier: -