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In the database of information system, usually there are some attributes which are unimportant to the decision attribute, and some records that disturb the decision making. In this paper, reducing the condition attributes based on the matter-element theory and rough set method, calculating the importance to the decision attribute for each condition attribute after reduction, and data mining the relevant...
In the data base of information system, usually there are some attributes which are unimportant to the decision attribute, and some records that disturb the decision making. In this paper, reducing the condition attributes based on the matter-element theory and rough set method, calculating the importance to the decision attribute for each condition attribute after reduction, and data mining the relevant...
The problem of imperfect knowledge has been tackled for a long time by philosophers, logicians and mathematicians. The main idea of rough set theory is to extract decision rules by attribute reduction and value reduction in the premises of keeping the ability of classification, reducing the condition attributes based on the extension set theory and rough set method, calculating the importance to the...
The advanced management idea of "Take the customer as the center" manifests fully in the customer segmentation. Customer segmentation may meet customer need at whole hog enable the enterprise to achieve the maximal profit. Extension data mining is an advanced effective data analysis method. Its application to enterprise brands segmentation will help the enterprises to gain their ends on...
Knowledge sharing in VCs heavily relies on members?? interaction, which takes participants?? time and effort to collaborate, and the costs of and benefits from interactions in knowledge sharing vary with different collaborator selection. To achieve efficient and effective knowledge sharing, strategic interactions are needed. In this paper, we tried to tackle the strategic interaction support problem...
Since decision variables like criteria value and weighting factors can be influenced by subjective and objective variations, sensitivity analyses are crucial for the effectiveness of decision support systems. In this paper, a systematic analytical approach is demonstrated, by which sensitivity indicators are derived for each criteria weight. Furthermore, an optimization model is presented to determine...
A hybrid inference framework is presented in which the aim is to select decision models through natural language in knowledge-based decision support system. In situations in which the rules that determine a system are uncertain and incomplete, the knowledge elicitation, maintenance and update of the rule-based system can be the problematic tasks. In such a situation, it has been found that a hybrid...
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