【摘要】 推荐系统已成为数字图书馆个性化服务不可缺少的一项重要技术。目前的推荐方法主要是基于规则的推荐和协同过滤方法,这两种方法都有其优缺点,它们共同的缺点是没有考虑语境信息对推荐的影响,从而导致推荐结果不佳。在分析语境信息在推荐过程中的作用的基础上,把语境信息集成到多维推荐模型中,利用数据仓库和OLAP处理层级式聚合计算的能力,建立具有多维信息收集与分析的推荐框架,并做了模块的分析。更多还原

【Abstract】 It has been recognized that recommendation system is a very important and indispensable topic in digital library.Personalized recommendation methods are mainly classified into content-based recommendation approach and collaborative filtering recommendation approach.Their common drawback is that context information does not take the impact of the recommendation,resulting in poor recommendation results.In analyzing the contextual information in the course of the role of the recommendation,the paper proposes the integrated contextual information as the foundation concept of multidimensional recommendation model,and uses the OLAP ability of data warehousing to solve the contradicting problems among hierarchy ratings,establishesa framework for multidimensional information gathering and analyzing,and analyzesthe relative modules.更多还原