关键词: 微博网站, 隐主题, 聚类, 权威信息

Abstract: Aiming at the inherent sparsity and strong timeliness about microblog, this paper studies the retrieval problem of topic-oriented authoritative information in microblog site. Firstly, this paper presents the method extracting the implicit theme of microblog, which can effectively ease sparsity problem about microblog short text data. Furthermore, this paper uses a two-stage clustering algorithm into microblog site to classify information by topics, which can speed up searching time. Finally, this paper proposes an efficient rank model in microblog site, which combines pseudo relevance feedback technology of KL-divergence language model and time factor for rank, and uses the first-retrieved microblog information of home page with high retweeting numbers to conduct query expansion. The experimental results on real datasets from Sina microblog demonstrate that the proposed implicit theme model can considerably solve data sparseness problem, and the rank model of authoritative information has better performance in terms of real-time information search.

Key words: microblog site, implicit theme, clustering, authoritative information