Personalized Recommendation Algorithm Based on Fuzzy Semantics in Big Data Environment

With the continuous expansion of the scale of e-government, personalized recommendation technology has been widely used. However, the traditional recommendation system has been unable to meet the needs of the current data processing, and good big data processing ability has become the basic requirement of the new personalized recommendation system, Combined with the application background of big data: firstly, this paper puts forward the construction method of personalized information service system with portal as the core, including the construction object, mode, goal and principle system. After information integration, in order to improve the security of the system, the authority management and access control are introduced. Secondly, a unified model is established to describe the integration of information resources and user files. Thirdly, the data mining method is used to discover the user's interest in integrated information. Combined with Hadoop cloud computing platform, the distributed construction of the model is realized, and the stability of the classic collaborative filtering algorithm is improved. Finally, a fuzzy semantic model of personalized recommendation system is proposed and implemented with a fuzzy description logic language.