Harleen Kaur

Work place: Department of Computer Science, Hamdard University, New Delhi, India

E-mail: harleen_k1@rediffmail.com


Research Interests: Logic Circuit Theory, Logic Calculi, Information Retrieval, Computer Graphics and Visualization, Medical Informatics


Harleen Kaur gained her Ph.D. in Computer Science from Jamia Millia Islamia University, New Delhi, India on the topic of Applications of Data Mining techniques in Health care Management. She graduated from the University of Delhi, New Delhi. She has previously served as a Lecturer in Computer Science, University of Delhi. Currently, she is an Assistant Professor at the Department of Computer Science, Hamdard University. She has published numerous research articles in refereed international journals and conference proceedings and chapters in an edited book. She is a member of several international bodies. Her main research interests are in the fields of Data analysis with applications to medical databases, Medical decision making, Fuzzy logic, Information Retrieval, Bayesian networks and visualization.

Author Articles
A Multi-intelligent Agent System for Automatic Construction of Rule-based Expert System

By Mohammed Abbas Kadhim M. Afshar Alam Harleen Kaur

DOI: https://doi.org/10.5815/ijisa.2016.09.08, Pub. Date: 8 Sep. 2016

The main general purpose of this research is the automatic construction of rule-based expert system in diagnosis domain based on an expert system tool and a multi-intelligent agent system. The first goal is used an expert system tool (shell) which is called Diagnosis Domain Tool for Rule-based Expert System (DDTRES) [1]. The second goal is used a multi-intelligent agent architecture for knowledge extraction to elicit knowledge from its resources (domain experts, text documents, databases) for automatic construction of a knowledge base. That means, instead of using traditional methods for knowledge base construction, we used automatic way for that job. In order to achieve second objective, the following agents have been used: The Expert Mining Intelligent Agent (EMIA), The Text Mining Intelligent Agent (TMIA) [2], and The Multi-Intelligent Agent for Knowledge Discovery in Database (MIAKDD) [3]. We are aim to produce an effective final knowledge base by cooperation between EMIA, TMIA, and MIAKDD approaches and integrated with the diagnosis domain tool (DDTRES) to produce a complete rule-based expert system in diagnosis domain. We applied the captured rule-based expert system on heart diseases diagnosis, we found system performance is between a good and a very good range.

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