Knowledge base system visualization reasoning model based on ICON

Deyun Chen; Shujun Pei; Zhiying Quan

doi:10.1117/12.596954

28 March 2005 Knowledge base system visualization reasoning model based on ICON

Deyun Chen, Shujun Pei, Zhiying Quan

Proceedings Volume 5812, Data Mining, Intrusion Detection, Information Assurance, and Data Networks Security 2005; (2005) https://doi.org/10.1117/12.596954
Event: Defense and Security, 2005, Orlando, Florida, United States

Abstract

Knowledge base system is one of the most future branches for artificial intelligence facing with practical application. But the reasoning process of system is invisible, not visual and users cannot intervene the reasoning process, therefore for users the system is only a black box. This condition causes many users to take a suspicious attitude to the conclusions analyzing and drawing from the system, that means even though the system has the explanation function, but it is still not far enough. If we adopt graph or image technique to display this reasoning procedure interactively and dynamically which can make this procedure be visual, users can intervene the reasoning procedure which can greatly reduce users’ gain giving, and at the same time it can provide a given method for integrity check to knowledge of the knowledge base. Therefore, we can say that reasoning visualization of knowledge base system has a further meaning than general visualization. In this paper the visual problem of reasoning process for knowledge base system on the basis of the formalized analysis for ICON system, Icon operation, syntax and semanteme of the statement is presented, a reasoning model of knowledge base system that has a visual characteristics is established, the model is used to do an integrity check in practical expert system and knowledge base, better effect is got.

Citation Download Citation

Deyun Chen, Shujun Pei, and Zhiying Quan "Knowledge base system visualization reasoning model based on ICON", Proc. SPIE 5812, Data Mining, Intrusion Detection, Information Assurance, and Data Networks Security 2005, (28 March 2005); https://doi.org/10.1117/12.596954

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