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[会议论文]

Word sense disambiguation of semantic document

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Author:

Shi, Bin (Shi, Bin.) | Fang, Liying (Fang, Liying.) | Yan, Jianzhuo (Yan, Jianzhuo.) | Unfold

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EI Scopus

Abstract:

A Max-Probability Density based Clustering (MPDC) algorithm is proposed in this paper to resolve the problem of Word Sense Disambiguation in semantic document. MPDC take the context information of a keyword based on WordNet into account and select the max probability sense by measuring the density of the concept. We also do experiment on semantic documents retrieving from Swoogle and Watson, two famous semantic web searching engines. The result shows MPDC get a good efficiency. ©2010 IEEE.

Keyword:

Natural language processing systems Clustering algorithms Ontology

Author Community:

  • [ 1 ] [Shi, Bin]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124, China
  • [ 2 ] [Fang, Liying]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124, China
  • [ 3 ] [Yan, Jianzhuo]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124, China
  • [ 4 ] [Wang, Pu]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124, China

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Source :

Year: 2010

Volume: 3

Page: V3224-V3228

Language: English

Cited Count:

WoS CC Cited Count: 0

30 Days PV: 3

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