Disambiguated query suggestions and personalized content-similarity and novelty ranking of clustered results to optimize web searches

In this paper, we face the so called “ranked list problem” of Web searches, that occurs when users submit short requests to search engines. Generally, as a consequence of terms’ ambiguity and polysemy, users engage long cycles of query reformulation in an attempt to capture relevant information in the top ranked results.     

个性化服务中挖掘用户兴趣的CMPS

针对数字图书馆个性化服务的发展趋势，指出掌握用户兴趣是数字图书馆实现个性化的主动信息服务的基础性前提。阐述了三种兴趣挖掘方法的利弊，提出综合利用三种方法来获取用户兴趣的CMPS系统，并给出了具体的方法。     

Web环境下的个性化信息检索技术

对当前网络环境下应用的若干典型的个性化信息检索技术进行了研究和分析。介绍了个性化信息检索的一般模型，从四个不同的角度对各种个性化检索技术做了分类，列举了主要的个性化检索个案，描述了个性化检索系统的核心模块，并简单介绍了如何提高个性化检索的效率。     

基于Ontology的个性化信息服务系统框架*

个性化信息服务是信息检索系统的发展趋势，强调对用户服务的针对性和服务特色。文章分析总结了典型的个性化服务模式、关键技术及其研究现状。在此基础上，提出了基于Ontology的个性化信息服务系统框架，对系统的结构和主要处理流程进行了探讨。     

泰达图书馆个性化信息服务系统的探索与实践

介绍了泰达图书馆在开展个性化信息服务方面的探索性成果，根据两个个性化信息服务系统：个性化信息推送系统和Mylibrary系统的实践，提出了个性化信息服务系统发展和完善的思路。     

个人数字图书馆

介绍了个人数字图书馆中个人文档的组成元素及模式，个人数字图书馆中信息的组织形式,以及通过积极阅读实现信息的增值服务。     

个性化服务中的网络体育信息资源整合研究

网络环境下体育信息资源的数量和存在方式都发生了变化。因此,如何将体育数字信息资源整合起来,以向使用者们提供个性化的体育信息服务,成为体育信息资源开发与利用的关键。文章在分析了网络体育信息资源特点的基础上,提出了基于个性化知识门户的体育信息集成构想．建立基于个性化服务的体育信息资源整合平台。     

The influence of personalization on tag query length in social media search

Social content systems contain enormous collections of unstructured user-generated content, annotated by the collaborative effort of regular Internet users. Tag-clouds have become popular interfaces that allow users to query the database of these systems by clicking relevant terms. However, these single click queries are often not expressive enough to effectively retrieve the desired content. Users have to use multiple clicks or type longer queries to satisfy their information need.     

A group recommendation system for online communities

Online communities are virtual spaces over the Internet in which a group of people with similar interests or purposes interact with others and share information. To support group activities in online communities, a group recommendation procedure is needed. Though there have been attempts to establish group recommendation, they focus on off-line environments. Further, aggregating individuals’ preferences into a group preference or merging individual recommendations into group recommendations—an essential component of group recommendation—often results in dissatisfaction of a small number of group members while satisfying the majority. To support group activities in online communities, this paper proposes an improved group recommendation procedure that improves not only the group recommendation effectiveness but also the satisfaction of individual group members. It consists of two phases. The first phase was to generate a recommendation set for a group using the typical collaborative filtering method that most existing group recommendation systems utilize. The second phase was to remove irrelevant items from the recommendation set in order to improve satisfaction of individual members’ preferences. We built a prototype system and performed experiments. Our experiment results showed that the proposed system has consistently higher precision and individual members are more satisfied.     

基于用户兴趣的个性化搜索系统研究

针对目前常用搜索引擎在查询时返回结果数量巨大且杂乱无章的现象,在Web客户端为实现对用户的个性化信息服务设计了一种基于用户兴趣的搜索系统。利用用户的兴趣对于用户提出的搜索条件进行处理,再通过常用的搜索引擎进行查询,并将得到的结果进行二次排序,同时通过反馈信息不断更新用户的兴趣,以满足用户不断变化的需求。实验证明这样在保证了查全率的基础上,提高了查准率,从而提高了搜索效率。