基于博主背景的博客倾向性检索归一化策略

A Blog-Profile Based Normalization Strategy for Blog Opinion Retrieval

博客倾向性检索的目标是检索出不仅与特定查询主题相关而且包含针对该主题的评论的博文单元,并依据倾向性强度进行排序。目前大多数研究工作仅仅通过单个博文单元包含的主题倾向性强弱对博文进行排序。然而,博客是博主表达自己观点情感的媒介,博主的个性风格很大程度上影响着倾向性强度,忽略博主因素仅仅使用单个博文单元获取倾向性评分,会给倾向性评分带来偏差。针对这个问题,该文首先分析博主背景因素对倾向性评分的影响并建立博主背景模型,然后提出基于博主背景的博客倾向性检索归一化策略,最后使用该策略对基于概率推理模型的博客倾向性检索算法进行归一化。实验结果表明,基于博主背景的倾向性检索归一化策略能够更加合理地对博主单元进行排序。

The goal of Blog Opinion Retrieval is to retrieve the blog units that not only relate to a given query but also comment on the query. Previous works ranked blog units by the opinion strength of a single blog unit. However, since blog is the media expressing the btogger＇s opinions and feelings, the personality of a blogger could affect the strength of his opinion. Therefore, it is disadvantageous defect to use only a single blog unit to get opinion score while neglecting the blogger＇s factor. In this paper we build a hlogger profile and then present a blogger-profile based normalization strategy for blog opinion retrieval. We apply it to normalize the Blog Opinion Retrieval algorithm based on probabilistic inference model. Experiment results show that the proposed normalization strategy could rank blog units more reasonably and improve the retrieval performance.