Application of Cloud Model in Personalized Service Recommendation of Web Log Mining

Personalized service recommendation is a hot research spot of web log mining in the application realm. Through introducing the related theories of web log mining and personalized service, analyzing the status quo of personalized service recommendation of web log mining, combining with basic theories of cloud model and its feasibility and superiority in web log mining, the author promotes a personalized service recommendation model in web log mining based on cloud model. This model utilizes the uncertain reasoning algorithm of cloud, handles with the randomness and obscurity of web log data and realizes the mutual exchange between qualitative and quantitative of user´s personalized service recommendation language value. Finally, the experimental simulation of recommendation model illustrates that the application of cloud model improves the accuracy of personalized service recommendation of web log mining and is possessed of dependability and validity.