Mining the Web for Knowledge with Sub-Optimal Mining Algorithm
COMPSAC '00 24th International Computer Software and Applications Conference
Information Sciences: an International Journal
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Fuzzy Optimization and Decision Making
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IRI'09 Proceedings of the 10th IEEE international conference on Information Reuse & Integration
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IEEE Transactions on Fuzzy Systems
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Expert Systems with Applications: An International Journal
Computing with words for hierarchical decision making applied to evaluating a weapon system
IEEE Transactions on Fuzzy Systems - Special section on computing with words
IEEE Transactions on Fuzzy Systems - Special section on computing with words
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AIS'11 Proceedings of the Second international conference on Autonomous and intelligent systems
A reconstruction decoder for computing with words
Information Sciences: an International Journal
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Computing with words is defined, in this paper, to be a symbolic generalization of fuzzy logic, which admits self-reference. It entails the randomization of declarative knowledge, which yields procedural knowledge. Such randomization can occur at two levels. First is termed weak randomization, which is essentially a domain-general pattern-matching operation. Second is termed strong randomization, which entails the application of one rule set to the semantics of another-possibly including itself. Strong randomization rests on top of weak randomization. Strong randomization is essentially a heuristic process. It is fully scalable, since it can in theory map out its own needed heuristics for evermore efficient search-including segmentation of the knowledge base. It is proven that strong learning must be knowledge-based, if effective. Computing with words does not preclude the use of predicate functions or procedural attachments. Also, the paradigm for computing with words does not directly compete with that for fuzzy logic. Rather, it serves to augment the utility of fuzzy logic through symbolic randomization. A countably infinite number of domain-specific logics or knowledge-based methods for randomization exist