Fuzzy sets, uncertainty, and information
Fuzzy sets, uncertainty, and information
Integrating expert systems with group decision support systems
ACM Transactions on Information Systems (TOIS)
Fuzzy specification in data capture and knowledge representation for an expert system in oncology
Fuzzy Sets and Systems - Special issue on fuzzy expert systems
Fuzzy logic and knowledge representation using linguistic modifiers
Fuzzy logic for the management of uncertainty
Inside a software design team: knowledge acquisition, sharing, and integration
Communications of the ACM
Communications of the ACM
Fuzzy logic for business and industry
Fuzzy logic for business and industry
Fuzzy Expert Systems Tools
Decision Support Systems and Intelligent Systems
Decision Support Systems and Intelligent Systems
KDA: A Knowledge-Based Database Assistant with a Query Guiding Facility
IEEE Transactions on Knowledge and Data Engineering
Expert Systems: A View of the Field
IEEE Expert: Intelligent Systems and Their Applications
AI Models for Business Process Reengineering
IEEE Expert: Intelligent Systems and Their Applications
Web-based expert systems: benefits and challenges
Information and Management
An expert system using an extended AND-OR graph
Knowledge-Based Systems
Web-based expert systems: benefits and challenges
Information and Management
A hybrid tele-diagnosis system on fish disease
ACOS'06 Proceedings of the 5th WSEAS international conference on Applied computer science
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A convergence of Internet and fuzzy logic technologies provides an opportunity for experts and end users to collaborate in developing, refining, and testing knowledge-based systems. Internet technology removes geographical and time-based restraints, and fuzzy rule bases are easier to understand and maintain. This paper describes an architecture and a prototype for developing, delivering, and maintaining expert systems on the World Wide Web.The system's collaboration components allowed experts to monitor user consultations remotely, view summaries of responses, and trace-rule inference chains. Experts and users participated in real-time chat sessions or posted questions on extended discussion lists. The system allowed experts and users to experiment with real-time enhancements of knowledge bases. Fuzzy rules resulted in semantically richer knowledge bases that flexibly handled complex and uncertain knowledge. A fuzzy inference engine supported hedges and partial matching to assist users in applying knowledge and exploring Web-based data.