基于社会化标注和网页分类的个性化检索方法

Web2.0为信息检索提供了很多可以使用的资源,其中两种资源对于个性化检索而言非常有益,那就是社会化标注和网页分类信息。用户给出的标签反映了其对于网页的认识和思考,而用户标注过的网页的类别则反映了用户在选择时的偏好和兴趣,两者的结合使用对个性化检索能起到良好的效果。在仅使用社会化标注进行个性化检索的方法上,提出基于标注和网页分类进行个性化检索的方法,通过两者结合筛选出兴趣和偏好相近的用户,进行用户属性的扩展,并在扩展时考虑用户的质量,从而能在个性化检索中取得更好的结果。在真实数据集上的实验表明,本文方法具有一定的优势。

Personalized search based on folksonomy and category

Web 2.0 has provided information retrieval with many useful resources. Two kinds of them are beneficial for personalized search, which are social annotations and categorical information. The annotations that user gives come from his consideration, and the categories of the documents that he annotated reflect his preference and interest. So combining these two kinds of resources will benefit the personalized search. Our work is based on a personalized searching method with only annotations, and we propose a method based on both annotations and categorical information. We use them to screen similar users in preference and interest to extend users profile, so that user extended profile will be more accurate. The experiment based on real dataset proves that our method has superiority.