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It has very realistic significance for improving the quality of users’ accessing information to filter and selectively retrieve the large number of information on the Internet. On the basis of analyzing the existing users’ interest models and some basic questions of users’ interest(representation,derivation and identification of users’ interest) ,a Bayesian network based users’ interest model is given. In this model,the users’ interest reduction algorithm based on Markov Blanket model is used to reduce the interest noise,and then users’ interested and not interested docu-ments are used to train the Bayesian network. Compared to the simple model,this model has the following advantages like small space requirements,simple reasoning method and high recognition rate. The experiment result shows this model can more appropri-ately reflect the user’s interest,and has higher performance and good usability.
It has very realistic significance for improving the quality of users’ access information to filter and selectively retrieve the large number of information on the Internet. On the basis of analyzing the existing users’ interest models and some basic questions of users’ interest (representation, derivation and identification of users’ interest), a users’ interest reduction algorithm based on Markov Blanket model is used to reduce the interest noise, and then users’ interested and not Compared to the simple model, this model has the following advantages like small space requirements, simple reasoning method and high recognition rate. The experiment result shows this model can more appropri-ately reflect the user’s interest, and has higher performance and good usability.