Word sense disambiguation of semantic document - Details

Author：

Shi, Bin (Shi, Bin.) | Fang, Liying (Fang, Liying.) | Yan, Jianzhuo (Yan, Jianzhuo.) | Wang, Pu (Wang, Pu.)

Indexed by：

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