Hongxin Wan

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There are many uncertainties of the data in information systems, which affects the extraction of decision rules. Using rough set to deal with these non-precise data can achieve effective decision-making rules by deleting redundant attributes. Through the relationship of key attributes, we can get association rules in a higher interested degree. The rules(More)
Adaptive testing is a form of intelligent computer test. The number and types of the exam questions are uncertain. How to design high reliability algorithms to reflect the real level of the candidates is the key problem, also it is the most difficult problem. The realizing algorithms of parameter set, iterative computation and answer information estimation(More)
The e-commerce goods classification can put the products of similar nature and characteristics into the same cluster, but the huge amount of data of goods will cause classification algorithm in a high degree of complexity. On the premise of not influencing the classification results, how to reduce the size of the original product data, eliminate noise data(More)
E-commerce commodities contain a large number of associated information, an algorithm on how to mine association rules based on rough set is proposed in this paper. The different feature vectors extracted from different types of commodities can be looked as a prerequisite for getting association rules. By using the knowledge reduction theory the associated(More)
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