多维信息推荐是目前信息推荐领域中的一项新技术,能动态获取用户在不同情景下的兴趣变化,向用户提供更加个性化、智能化的推荐结果。本文介绍了多维信息推荐的相关知识,提出了输出情景化这一新的概念,构建了基于输出情景化的多维信息推荐系统模型,研制出基于输出情景化的多维信息推荐算法,并通过实验研究方法验证了所提出的多维信息推荐算法的高效性与优越性。
Multi-dimensional information recommendation(MDIR) is a new technology in the field of information recommendation. MDIR can dynamically catch the users' interest changes in different contextsand provide more individualized and intellectualized results. This paper firstly introduces the related content of MDIR. Secondly the paper brings forth the new concept: contextual post-filtering. Thirdly, the paper builds up a new multi-dimensional information recommendation model based on contextual post-filtering and designs a new multi-dimensional recommendation algorithm. Finally, the paper adopts an experiment to test and verify the high efficiency of the new algorithm.