基于相关反馈的微博相似主题时序查询

摘要

A new approach based on relevance feedback was proposed for the topic time series similarity search in micro-blogging. By considering whether the user is satisfied with the returned time series, we established an objective function for learning the coefficient of the unique metric,which reflects the user's accurate interest Therefore, the approach can provide the user with more satisfying topic time series in micro-blogging. We also developed a topic time series similarity search system in micro-blogging based on the new approach. Experiment results on Twitter data show the effectiveness of our proposed approach.%提出了一种基于相关反馈的微博相似主题时序查询方法.该方法通过考虑用户对不同查询结果是否满意的反馈情况,建立修改度量系数的目标函数,从而实现微博中体现用户兴趣的主题时序相似性计算,为用户提供更满意的相似主题时序查询结果.基于该方法设计了一个可视化的微博相似主题时序查询系统,在微博代表性网站-Twitter数据集上进行的实验,表明了该方法在微博背景下的相似主题时序查询中的有效性.