Information Recommendation System Based On User Preference Mining And Topic Search Technique

The asymmetry between the Web user requirement and massive Web information is becoming an escalating problem with the rapid increase of the Web pages and users. Consequently, technologies to provide customized information search are booming like flowers after a spring rain. Among them is the customized information push based on user preference mining in e-commerce. All transactions of e-commerce are stored on the servers, which builds a solid ground for data mining. While we can mine with a certain precision users' preference, personalized recommendation services can be easily implemented. On the other hand, focused search technology is now capable of clustering topic-related information. Combining the two technologies to provide personalized information recommendation is the main theme of this paper.The Information Recommendation System (IRS) presented in this paper is based on user preference mining and focused information search and serves as a complementary service of e-commerce to provide guidance information to Web users. The IRS is comprised of three modules, namely information classified module, user preference mining module and focused search module. The IRS do a good integration with two technologies through good design, and two technology both use vector space model technology to be achieved. The system design of based on vector derived from the vector-based information retrieval technology, the technology in the information retrieval field to be changed and improved, thus becoming the technology adapting to the system. First, the system mines a certain period of historical data to obtained user preference. Then, corresponding user preference the system selects the information from the focused search's result. Finally, the system recommends the editorial information to the user. Meanwhile, the experimental data showed by the paper display that the system has good performance: improved Apriori algorithm greatly improved the operation efficiency, Vector-based data mining model with a higher matching accuracy, Vector-based focused search classifier with better performance.