In this chapter, we presents iJADE InfoSeeker, an intelligent context-aware agents 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 advantages of using multiple intelligent agents to mine news articles on the web, 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. iJADE InfoSeeker also demonstrates the advantages of using ontologies to identify topics. We use a Chinese document corpus to evaluate iJADE InfoSeeker and the testing result was compared to other approaches. It was found that the accuracy of identifying the topics of Chinese web articles is nearly 87%. It demonstrated a fast processing speed of less than one second per article. It also organizes content flexibly and understands knowledge accurately, unlike traditional text classification systems.
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Lim, E.H.Y., Lee, R.S.T. (2007). iJADE InfoSeeker: On Using Intelligent Context-Aware Agents for Retrieving and Analyzing Chinese Web Articles. In: Lee, R.S.T., Loia, V. (eds) Computational Intelligence for Agent-based Systems. Studies in Computational Intelligence, vol 72. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73177-1_5
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