DocumentCode :
2905210
Title :
KnowledgeSeeker — an ontological agent-based system for retrieving and analyzing Chinese web articles
Author :
Lim, Edward H Y ; Lee, Raymond S T ; Liu, James N K
Author_Institution :
Dept. of Comput., Hong Kong Polytech. Univ., Hong Kong
fYear :
2008
fDate :
1-6 June 2008
Firstpage :
1034
Lastpage :
1041
Abstract :
In this paper, we present the KnowledgeSeeker, an ontological agent-based system that is designed to help users find, retrieve, and analyze news article from the Internet and then present the content in a semantic web. We present the benefits of using ontologies to analyze the semantics of Chinese text, and also the advantages of using a semantic web to organize information semantically. KnowledgeSeeker also demonstrates the advantages of using ontologies to identify topics. We use a Chinese document corpus to evaluate KnowledgeSeeker and the testing result was compared to other approaches. KnowledgeSeeker is able to identify the topics of Chinese web articles with an accuracy of nearly 87% and has a processing speed of less than one second per article. It is also able to organize content flexibly and understands knowledge more accurately than methods that use ontology definition.
Keywords :
information analysis; information retrieval; ontologies (artificial intelligence); semantic Web; text analysis; Chinese Web articles; Chinese document corpus; Chinese text; Internet; KnowledgeSeeker; news article retrieval; ontological agent-based system; semantic Web; Content based retrieval; HTML; Information analysis; Internet; Machine intelligence; Ontologies; Search engines; Semantic Web; Testing; Web sites;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems, 2008. FUZZ-IEEE 2008. (IEEE World Congress on Computational Intelligence). IEEE International Conference on
Conference_Location :
Hong Kong
ISSN :
1098-7584
Print_ISBN :
978-1-4244-1818-3
Electronic_ISBN :
1098-7584
Type :
conf
DOI :
10.1109/FUZZY.2008.4630497
Filename :
4630497
Link To Document :
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