Network behavior based personalized recommendation method and system

Abstract

The invention discloses an individualized recommendation method based network behaviors. The method includes the following steps: (A). Generate the corresponding network behavior log of the user according to the search request sent by the users to the server and the report on the completion of document download, and record the keyword searched by users and downloaded document; (B). Analyze and clean up network behavior log, and modify system knowledge database and user matching database; (C). Find out users with the same interest from the modified user matching database and introduce them to users, and take the documents that users are interested in as the recommended document resource for users. The invention also discloses an individualized recommendation system based on network behaviors, which consists of network behavior log generating module, log analysis handling module, recommendation generating module, knowledge database, and user matching database. The invention has the advantages of high operating efficiency, strong usability of results, easy maintenance and expansion of the system, and capability to trigger users' interest.

Description

technical field [0001] The invention relates to a method and system for providing personalized recommendation service for users based on analyzing their network behavior. Specifically, the present invention relates to a method of analyzing the network behavior of each user, such as searched keywords and downloaded files, extracting similarities between users, and based on this, two aspects of personalized recommendations are made to users, such as A method and system for a user to recommend friends who have common interests with them and various files that may be of interest to them. Background technique [0002] With the rapid development of computer network technology, the Internet has become an important platform for people to obtain and exchange information. In this context, how to enable users to quickly and accurately find the content they need and are interested in in the information ocean of the Internet has become an urgent problem to be solved for the further deve...

AI Technical Summary

Problems solved by technology

The more rules, the higher the accuracy of the recommendation, but the more difficult the maintenance of the system, the performance will drop sharply

The content-based filtering system recommends resources to users by calculating the similarity between user behavior characteristics and resource characteristics. The disadvantages of this method are: it is difficult to distinguish the quality and style of resources, and it cannot find new interesting resources for users.

The collaborative filtering system is similar to the content-based filtering system, but it compares the similarity between different users, finds several most similar neighbor users, and predicts the user's interest through the neighbor users, so as to recommend resources to the user. The disadvantage of the method is: the initial system is sparse and the scalability is poor

[0008] 3. The nodes in the P2P system are unstable

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