KDIST: a development environment for knowledge discovery system
Zhenglong Wu, Wang Ruijing, Xiong Fanlun
Abstract
Zhenglong Wu, Wang Ruijing, Xiong Fanlun
Abstract
The paper presents a universal development environment of application domain-oriented knowledge discovery system - KDIST. Based on graphic modeling and intelligent guidance techniques, KDIST is user-friendly enough for generic people to develop a knowledge discovery system with expertise as little as possible. Not only discovering knowledge from data with high performance, but can the developed knowledge discovery system add discovered knowledge to a relative knowledge base and then refine knowledge on the premise of keeping consistence of the knowledge base.
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The paper presents a universal development environment of application domain-oriented knowledge discovery system - KDIST. Based on graphic modeling and intelligent guidance techniques, KDIST is user-friendly enough for generic people to develop a knowledge discovery system with expertise as little as possible. Not only discovering knowledge from data with high performance, but can the developed knowledge discovery system add discovered knowledge to a relative knowledge base and then refine knowledge on the premise of keeping consistence of the knowledge base.
Key concepts: Knowledge extraction, Knowledge base, Computer science, Domain knowledge, Knowledge-based systems, Premise, Open Knowledge Base Connectivity, Software mining