NDLI: A new Methodology of Mining Cognitive Maps

Content Provider	IEEE Xplore Digital Library
Author	Chen Zhuang Montazemi, A.R.
Copyright Year	2007
Description	Author affiliation: Chongqing Inst. of Technol., Chongqing (Chen Zhuang)
Abstract	Cognitive map (CM) is a new intelligent method. Compared either experts system and neural networks, it has several desirable advantages such as: it is relative easy to use for representing structured knowledge, and the inference can be computed by numeric matrix operation instead of explicit IF/THEN rules. However, in order to exhibit these advantages about CM, the first step is that the corrected CMs must be obtained. Traditional approaches for obtaining the CMs, including questionnaire method, brainstorming method and sample learning method, mainly rely on experience of domain experts. Because these methods put much emphasis on the subjective factors, neglect the objective data resources, they always lose some information. Therefore, this paper proposes a new methodology of mining the CMs based on data resource, which mainly includes database preprocessing technology, optimization algorithm for weight coefficients and simplification strategy of CMs. The experimental research based on a finance database is done and the results show that: the new method can mine all possible relationship among all nodes to form the CMs, and can also simplify it according to the significant degree of relationships; the CMs mined by the new method has more information than the CMs obtained by traditional approaches.
Starting Page	109
Ending Page	113
File Size	609002
Page Count	5
File Format	PDF
ISBN	9787811240559
DOI	10.1109/CHICC.2006.4346929
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-07-26
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Optimization methods Finance Collision mitigation Neural network Data mining Biological neural networks Computer science Learning systems Cognitive map Databases Learning arithmetic Computer networks Expert systems
Content Type	Text
Resource Type	Article

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