Concept hierarchy construction by combining spectral clustering and subsumption estimation

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with host publication)peer-review

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Detail(s)

Original languageEnglish
Title of host publicationWeb Information Systems - WISE 2006
Subtitle of host publication7th International Conference on Web Information Systems Engineering, Proceedings
PublisherSpringer Verlag
Pages199-209
Volume4255 LNCS
ISBN (Print)3540481052, 9783540481058
Publication statusPublished - 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4255 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Title7th International Conference on Web Information Systems Engineering, WISE 2006
PlaceChina
CityWuhan
Period23 - 26 October 2006

Abstract

With the rapid development of the Web, how to add structural guidance (in the form of concept hierarchies) for Web document navigation becomes a hot research topic. In this paper, we present a method for the automatic acquisition of concept hierarchies. Given a set of concepts, each concept is regarded as a vertex in an undirected, weighted graph. The problem of concept hierarchy construction is then transformed into a modified graph partitioning problem and solved by spectral methods. As the undirected graph cannot accurately depict the hyponymy information regarding the concepts, subsumption estimation is introduced to guide the spectral clustering algorithm. Experiments on real data show very encouraging results. © Springer-Verlag Berlin Heidelberg 2006.

Citation Format(s)

Concept hierarchy construction by combining spectral clustering and subsumption estimation. / Chen, Jing; Li, Qing.
Web Information Systems - WISE 2006: 7th International Conference on Web Information Systems Engineering, Proceedings. Vol. 4255 LNCS Springer Verlag, 2006. p. 199-209 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4255 LNCS).

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with host publication)peer-review