Recommended Study of the Flow of Information based on TF-IDF

Abstract

The methods to resolve Information overload can mainly classify two kinds: Information Retrieval and Information Filtering. Based on the needs of the people, Information Retrieval will search out the related information and technology from the information stored in some way. Information Filtering will choose out user preferred personalized information from the dynamic information flow based on the filtering requests of the people. The paper analyzed micro-blogs users needs and motivation, According to micro-blogs users motivation, effectively, an approach based on tem frequency inverse document frequency (TF-IDF) was proposed. This article constructed personalized recommendation models in on-line social streams based on ties strength, topic relevance and trust dimensions. The experiments on the Sina blogs data showed that the proposed method could reduce the ranks of irrelevant tweets effectively and achieve better performance than several baseline methods based on cosine and hash tags