IIPP-based personalized recommendation service

The size of Internet has been growing very fast and many documents appear every day in the Internet. Users find many problems to obtain the information that they really need. In order to help users in this task of finding relevant information, recommending systems were proposed. In this paper we will present our approach through the employment of "Information Push-Pull Technology". We take advantage of the complementary strengths of content-based and collaborative-based recommendation methods, applying topic-based Association Rules Mining to alleviate the synonymy problems and propose an Enhanced Vector Similarity (EVS) algorithm to reduce dimensionality and remedy the scalability problem Finally we demonstrate the effectiveness of our system in the rural information service.