中文摘要：

目的微博作为一个社交与信息分享平台，日信息量数以亿计，如何高效地搜索用户感兴趣的信息成为亟待解决的问题。提出了一个新颖的用户驱动的可视化微博信息搜索方法。方法采用特征词及其权重来建模用户的兴趣特征，并基于此建立用户与特征词之间的相关关系。搜索微博信息时，首先定位与检索词相关的微博用户，在相关微博用户的微博中筛选与搜索相关的微博。另外，采用关注度传递算法对搜索进行扩展，将返回的特征词和微博用户进行可视化展示，并提供交互供用户查看与选定特征词或用户相关的微博。结果实验结果表明，基于本文方法，用户可以高效地定位感兴趣的微博信息。结论以用户作为桥梁，大大缩小了微博信息的搜索范围，同时采用关注度传递算法对搜索进行扩展，对结果进行可视化展示。实验表明本文方法能够使用户快速搜索出感兴趣的信息。

英文摘要：

Objective As a social platform for sharing information, amicro-blog generates millions of information daily. Thus, searching for wanted information is difficult. Tosolve this problem, this paper proposes a novel user-driven visual microblog search method. Method The method usesfeature words to model the user＇s interest and to obtain the relationship between words and users based on the model. To search a relevant micro-blog, the method first locates micro-bloggers who arerelevant to the keywords and then filters micro-blogs. The method extends the query via anattention-diverting algorithm. Finally, the relevant users and feature words are visualized on the basis oftheir degree of relevance. An interactive interface is provided to enable users to search micro-blogs that are relevant to the feature words or users that they are interested in. Result We show through a case studythat users can efficiently find specific information by observing the visualization results and further interacting with the visualization interface. Conclusion We provide an efficient microblog search method that regardsmicro bloggers as a bridge to search for relevant microblogs and narrow down the search range. The proposed method also uses the attention-diverting algorithm to extend the query before the result is finally visualized. The proposed method is efficient and useful for users to find specific microblogs.