Similar variable precision rough set model-based knowledge pushing rule extraction method

Abstract

The invention discloses a similar variable precision rough set model-based knowledge pushing rule extraction method and belongs to the field of knowledge engineering. The method comprises the steps of extracting and processing user behavior data, establishing a decision table comprising condition attributes and decision attributes, obtaining the importance of the condition attributes relative to the decision attributes by utilizing an information entropy theory, and based on this, performing reduction on the decision table by utilizing the importance of the condition attributes relative to the decision attributes to obtain a reduced decision table; extracting a decision rule containing a certainty factor based on the reduced decision table; and performing verification assessment on a pushing rule, and after the rule assessment is passed, performing knowledge pushing by utilizing the rule, so that the knowledge pushing precision is improved. According to the method, the problem that the rough set model is excessively rigorous can be solved; the fault-tolerant capability of the rough set model can be improved; the method is suitable for a knowledge pushing rule extraction situation; and in addition, the high-quality knowledge pushing rule can be obtained, the knowledge pushing precision can be improved, the knowledge obtaining cost can be reduced, and the knowledge obtaining efficiency can be improved.

Description

technical field [0001] The invention relates to a method for extracting knowledge push rules based on a similar variable precision rough set model, belonging to the field of knowledge engineering. Background technique [0002] Knowledge push technology is to push the right knowledge to the right person at the right time, aiming to reduce the cost of knowledge acquisition and improve the efficiency of knowledge acquisition. The basis for knowledge push is mainly the situational conditions of knowledge generation and application, combined with knowledge push rules, to judge the knowledge that the current user needs, and push this knowledge to the user. The extraction of knowledge push rules is an important issue in the study of knowledge push. [0003] As a data analysis theory for dealing with uncertain information and knowledge, rough set has been widely and successfully applied in the fields of machine learning and knowledge discovery. Applying the theory of rough sets to...

AI Technical Summary

Problems solved by technology

[0004] Aiming at the following problems in the classic rough set model in the process of knowledge rule extraction in knowledge push: the classic rough set model is too strict, lacks fault tolerance, and is not suitable for the knowledge push rule extraction situation

A knowledge push rule extraction method based on a similar variable precision rough set model disclosed in the present invention can solve the problem that the rough set model is too strict, improve the fault tolerance of the rough set model, and make it suitable for the knowledge push rule extraction situation. In addition, the present invention The invention can obtain high-quality knowledge push rules, improve the accuracy of knowledge push, reduce the cost of knowledge acquisition, and improve the efficiency of knowledge acquisition

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