Artificial Intelligence
Building expert systems
Artificial intelligence (2nd ed.)
Artificial intelligence (2nd ed.)
Logical foundations of artificial intelligence
Logical foundations of artificial intelligence
Principles of artificial intelligence and expert systems development
Principles of artificial intelligence and expert systems development
Knowledge acquisition: principles and guidelines
Knowledge acquisition: principles and guidelines
Integration of weighted knowledge bases
Artificial Intelligence
Combining belief functions when evidence conflicts
Decision Support Systems
Expert Systems: Design and Development
Expert Systems: Design and Development
Decision Support Systems and Intelligent Systems
Decision Support Systems and Intelligent Systems
Handbook of AI
Merging element fuzzy cognitive maps
Proceedings of the 3rd International Conference on Ubiquitous Information Management and Communication
A modified fuzzy c-means algorithm for association rules clustering
ICIC'06 Proceedings of the 2006 international conference on Intelligent computing: Part II
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This paper discusses an automated process of merging conflicting information from disparate sources into a combined knowledge base. The algorithm provided generates a mathematically consistent, majority-rule merging by assigning weights to the various sources. The sources may be either conflicting portions of a single knowledge base or multiple knowledge bases. Particular attention is paid to maintaining the original rule format of the knowledge, while ensuring logical equivalence. This preservation of rule format keeps the knowledge in a more intuitive implication form as opposed to a collection of clauses with many possible logical roots. It also facilitates tracking using the support for each deductive result so that final knowledge in rule form can be ascribed back to original experts. As the approach is fairly involved mathematically, an automated procedure is developed.