Raymond S.T. Lee

Complete course on Intelligent Agent or AI with focus on contemporary and latest AI technologies and development Companion technical reference for agent developers/researchers who would like to adopt the iJADK toolkit to develop their own agent-based applications and projects The advanced section on modern ontology and ontological agents serves as research literature for AI researchers who would like to explore the advanced AI/agent topics that involve the contemporary research on ontological agents and applied ontology

From the AI Perspective to Modern Ontology

Fuzzy-Neuro Approach to Agent Applications

Edward H. Y. Lim

James N. K. Liu

The Knowledge Seeker is a useful system to develop various intelligent applications such as ontology-based search engine, ontology-based text classification system, ontological agent system, and semantic web system etc. The Knowledge Seeker contains four different ontological components. First, it defines the knowledge representation model ¡V Ontology Graph. Second, an ontology learning process that based on chi-square statistics is proposed for automatic learning an Ontology Graph from texts for different domains. Third, it defines an ontology generation method that transforms the learning outcome to the Ontology Graph format for machine processing and also can be visualized for human validation. Fourth, it defines different ontological operations (such as similarity measurement and text classification) that can be carried out with the use of generated Ontology Graphs. The final goal of the KnowledgeSeeker system framework is that it can improve the traditional information system with higher efficiency. In particular, it can increase the accuracy of a text classification system, and also enhance the search intelligence in a search engine. This can be done by enhancing the system with machine processable ontology.

Raymond S.T. Lee

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