Title :
Capturing Evolving Patterns for Ontology-based Web Mining
Author :
Li, Yuefeng ; Zhong, Ning
Author_Institution :
Queensland University of Technology, Australia
Abstract :
An ontology-based Web mining model tends to extract an ontology from user feedback and use it to search the right data from the Web to answer what users want. It is indubitable that we can obtain numerous discovered patterns using a Web mining model. However, some discovered patterns might include uncertainties when we extract them. Also user profiles are changeable. Therefore, the difficult issue is how to use and maintain the discovered patterns. This paper presents a theoretical framework for this issue, which consists of automatic ontology extraction, reasoning on the ontology and capturing evolving patterns. The experimental results show that all objectives we expect for the theoretical framework are achievable.
Keywords :
Ontology-based Web mining; data mining; data reasoning; ontology learning; pattern evolution; Ontologies; Web mining; Ontology-based Web mining; data mining; data reasoning; ontology learning; pattern evolution;
Conference_Titel :
Web Intelligence, 2004. WI 2004. Proceedings. IEEE/WIC/ACM International Conference on
Print_ISBN :
0-7695-2100-2
DOI :
10.1109/WI.2004.10040