2005Unpublished venueRequires access

KDIST: a development environment for knowledge discovery system

Zhenglong Wu, Wang Ruijing, Xiong Fanlun

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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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What this paper is about

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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Available 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.

Key concepts: Knowledge extraction, Knowledge base, Computer science, Domain knowledge, Knowledge-based systems, Premise, Open Knowledge Base Connectivity, Software mining

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