关键词: 短文本, 噪音, 话题发现, 动态性, 非线性时间, 基聚类器, 聚类集成

Abstract: The short text, randomness and a large amount of noise make the traditional methods of topic detection can not be solved to get the new topic, and these topic detection techniques have not considered the time factor of the microblog post. In this paper, the microblog topic detection method based on clustering ensemble is proposed for the characteristics of micro-blog and topic dynamic performance. This method considers the nonlinear time factor of microblog post, the improved K-Means method is used to construct the corresponding base cluster based on each feature of microblog, evaluate the effectiveness and difference between the each cluster, so as to set up the ensemble voting weights and the clustering ensemble is used for microblog topic detection. Experimental results show that the proposed method gets an accuracy up to 9.5% in microblog topic detection, which can detect the new topic more effectively.

Key words: short text, noise, topic detection, dynamic, nonlinear time factor, base cluster, clustering ensemble