Web service recommendation method based on socializing network platform

Abstract

The invention relates to a Web service recommendation method based on a socializing network platform. Web services are classified into different service classes, basic information of users in the socializing network is obtained, and partials users are taken as training users and service classes which attract the users are obtained, so that a user-service matrix is set up based on the service classes. User clustering is carried out according to the user-service matrix, so that different interests of the users are obtained. In terms of new users who need Web service recommendation in the socializing network, recommendation is carried out according to the interests of the users. According to the Web service recommendation method based on the socializing network platform, theme extracting is carried out on the Web services, and the Web services are mapped to be the Web service classes, so that dimensionality reduction is carried out on the user-service matrix. Basic information and interest labels of the users are extracted from the socializing network and label information and semantic information are fully utilized for solving the synonymy problem of words. A clustering result is obtained by analyzing historical access records of existing users and Web service recommendation is carried out on the new users.

Description

technical field [0001] The invention belongs to the technical field of computers, relates to a recommendation method in data mining, is used for automatically recommending Web services to users, and is a Web service recommendation method based on a social network platform. Background technique [0002] Web services provide services through standard Web protocols, thus ensuring that application services on different platforms can interoperate. With the development of Internet technology, the number of Web services has grown rapidly, which has brought about information overload while providing users with a variety of choices. Therefore, providing users with efficient and accurate Web service selection and recommendation algorithms has become a hot issue in the field of service computing. [0003] Among many alternative Web services with the same or similar functions, the QoS value (Quality-of-Service) is often used to describe the non-functional characteristics of the Web ser...

AI Technical Summary

Problems solved by technology

[0008] The problems to be solved by the present invention are: 1) With the increase of the number of users and services, the Web service recommendation algorithm needs to have the ability to deal with high-dimensional sparse matrix, and needs to give recommendation results in a short time; 2) The existing absolute Most of the recommendation systems cannot find the synonym problem between words, they will divide the words with the same or similar meaning into different categories, how to divide the words with the same meaning into one category in the clustering process; 3) in the collaborative Based on the filtering algorithm, how to solve the problem of cold start, that is, to find the connection between a new user and different groups of users in the clustering results

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