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Map-Based Recommendation of Hyperlinked Document Collections

机译:基于地图的超链接文档集推荐

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摘要

The increasing number of documents returned by search engines for typical requests makes it necessary to look for new methods of representation of the search results. In this paper, we discuss the possibility to exploit incremental, navigational maps based both on page content, hyperlinks connecting similar pages and ranking algorithms (such as HITS, SALSA, PHITS and PageRank) in order to build visual recommender system. Such system would have an immediate impact on business information management (e.g. CRM and marketing, consulting, education and training) and is a major step on the way to information personalization.
机译:搜索引擎针对典型请求返回的文档数量越来越多,因此有必要寻找代表搜索结果的新方法。在本文中,我们讨论了基于页面内容,连接相似页面的超链接以及排名算法(例如HITS,SALSA,PHITS和PageRank)利用增量导航地图的可能性,以构建视觉推荐系统。这种系统将对业务信息管理(例如CRM和市场营销,咨询,教育和培训)产生直接影响,并且是信息个性化方式的重要一步。

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