一种基于社会化标注的网页检索方法

利用社会化标注对网页检索进行改进，提出一种加权的社会化SimRank算法。从社会化标注系统中提取网页以及标签词之间的相似度信息。分别用这2类相似度信息来计算网页本身的质量同网页与查询之间的相关性。依据网页的质量和相关性信息对网页进行重排序。在del.icio.us网站抽取真实标注数据集进行实验，结果表明，该方法挖掘到的信息能够较好地改善网页检索效果。

Web Retrieval Method Based on Social Tagging

This paper concerns with the issue of how to enhance Web retrieval with social annotations.It proposes a weighted social SimRank algorithm to get the similarity information of pages and annotations from social tagging system.The two types of similarity information are used to calculate quality of the pages and the relevance between pages and queries,respectively.And the pages are reordered according to the pages’quality and relevance information.Experiments are carried out on a real-world annotation data set which is sampled from del.icio.us.Experimental results show the significant improvements over traditional methods and the effectiveness of the proposed algorithm.