Evolution and evaluation in knowledge fusion system
J Gou, J Yang, Q Chen�- …�: A Bioinspired Approach: First International Work�…, 2005 - Springer
J Gou, J Yang, Q Chen
Artificial Intelligence and Knowledge Engineering Applications: A Bioinspired�…, 2005•SpringerThe paper presents a method to control evolution of pattern in a knowledge fusion system. A
self-adapt evaluation mechanism to assign proper value dynamically to weight parameters
is also described. Some rules are defined with aid of the matrix theory to promise the
controllablity and describability to the evolution process. A new knowledge object, called
LKS (local knowledge state), that can redirect path in knowledge fusion system and evolve
to other knowledge object (s) is formed in that model. Experimental results of a case study�…
self-adapt evaluation mechanism to assign proper value dynamically to weight parameters
is also described. Some rules are defined with aid of the matrix theory to promise the
controllablity and describability to the evolution process. A new knowledge object, called
LKS (local knowledge state), that can redirect path in knowledge fusion system and evolve
to other knowledge object (s) is formed in that model. Experimental results of a case study�…
Abstract
The paper presents a method to control evolution of pattern in a knowledge fusion system. A self-adapt evaluation mechanism to assign proper value dynamically to weight parameters is also described. Some rules are defined with aid of the matrix theory to promise the controllablity and describability to the evolution process. A new knowledge object, called LKS (local knowledge state), that can redirect path in knowledge fusion system and evolve to other knowledge object(s) is formed in that model. Experimental results of a case study show that it can improve the efficiency and reduce computational complexity of a knowledge fusion system.
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