A Semantic Clustering Algorithm Oriented to Web Log

Author

Wu, Chen ; Dai, Jun ; Li, Qi-feng ; Zhu, Jun-wu

Author_Institution

Sch. of Electron. & Inf., Jiangsu Univ. of Sci. & Technol., ZhenJiang

fYear

2006

fDate

13-16 Aug. 2006

Firstpage

1566

Lastpage

1569

Abstract

Existed Web logs are lack of semantics obviously. To improve the efficiency and accuracy of Web mining, a semantic Web log model - SWLM is presented, and two algorithms based on this model is given to cluster pages and users. Firstly, this method defines ontologies to interpret properties of Web log, then computing the semantic distances of log concepts. Based on the set of terms defined by ontology, the semantic information can be mining from the Web log. The test experiment shows that this model has better performance and clusters pages and users effectively. Those results can facilitate personalized services and user modeling

Keywords

Web sites; data mining; ontologies (artificial intelligence); pattern clustering; semantic Web; user modelling; SWLM; Web mining; ontologies; personalized services; semantic Web log model; semantic clustering algorithm; semantic information; user modeling; Clustering algorithms; Cybernetics; Data mining; Machine learning; Ontologies; Programmable logic arrays; Resource description framework; Semantic Web; Space technology; Testing; Virtual colonoscopy; Web mining; Web pages; Web log; mining; ontolgol; semantic;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2006 International Conference on

Conference_Location

Dalian, China

Print_ISBN

1-4244-0061-9

Type

conf

DOI

10.1109/ICMLC.2006.258830

Filename

4028314