摘要
多媒体信息检索技术的一个研究热点是通过学习来对检索结果进行排序,而排序学习在数字图书馆信息检索中的应用也成为数字图书馆研究的一个新热点。本文分析了数字图书馆信息检索的现状和主流排序算法,特别着重分析现行经典排序算法PageRank,并在此基础上研究分析排序学习在数字图书馆个性化服务中的应用。结果表明排序学习在分析用户个性化需求,提高用户检索的查准率,满足用户个性化检索要求方面能够发挥重要作用。
One of the hotspot in the research of multimedia information retrieval technology is to rank the search results with learning. Applied in the information retrieval of digital libraries it also becomes a new focus in the digital library research. This paper analyzes the status quo of the information retrieval and the mainstream ranking algorithm in the digital library with a special consideration on the analysis of current classical ranking algorithm ＂PageRank＇, and the application of learning to rank in personalized service of the digital library. The paper comes to the conclusion that learning to rank plays an important role in analyzing user＇s requirements, improving users＇ precision ratio of information retrieval and meet users＇ personal needs of search
出处
《西安建筑科技大学学报（社会科学版）》
2010年第1期97-100,共4页
Journal of Xi'an University of Architecture & Technology(Social Science Edition)
关键词
排序学习
数字图书馆
信息检索
个性化服务
learning to rank
digital library
information retrieval
personalized service
