A Semantic Clustering Algorithm Oriented to Web Log

Chen Wu; Jun Dai; Qi-Feng Li; Jun-Wu Zhu

doi:10.1109/ICMLC.2006.258830

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A Semantic Clustering Algorithm Oriented to Web Log

Chen Wu, Jun Dai, Qi-Feng Li and Jun-Wu Zhu

2006 International Conference on Machine Learning and Cybernetics, Vol.2006, pp.1566-1569

08/2006

DOI: https://doi.org/10.1109/ICMLC.2006.258830

Handle:

https://hdl.handle.net/20.500.12741/rep:6650

Abstract

semantic

ontolgol

Ontologies

Resource description framework

mining

Data mining

Semantic Web

Space technology

Web log

Clustering algorithms

Web pages

Web mining

Programmable logic arrays

Testing

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

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Title: A Semantic Clustering Algorithm Oriented to Web Log
Creators: Chen Wu - Sch. of Electron. & Inf., Jiangsu Univ. of Sci. & Technol., ZhenJiang
Jun Dai - Sch. of Electron. & Inf., Jiangsu Univ. of Sci. & Technol., ZhenJiang
Qi-Feng Li
Jun-Wu Zhu
Academic Unit: Computer Science Department
Publisher: IEEE
Publication Details: 08/2006
Identifiers: 99257880244601671; https://hdl.handle.net/20.500.12741/rep:6650; https://doi.org/10.1109/ICMLC.2006.258830
Language: English

A Semantic Clustering Algorithm Oriented to Web Log

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