A personalized recommendation system based on case intelligence

Jianyang Li, Rui Li, J. Zheng, Zhihong Zeng
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引用次数: 2

Abstract

The acquisition of personalized need is key to effective recommendation. Case intelligence is a comprehensive expression which is integrated representation of human sense, logics and creativity. Through the former cases we can acquire users' preferences which are implicit in case-base, the process of recommendation is easy to understand and accept. As E-commerce is in complex environment, cases are regarded as the foundation for knowledge representation in case intelligent system and may be represented in semi-structured or unstructured model, or even in natural language texts. This paper presents a personalized recommendation system based on case intelligence. The system has good flexibility, uses modular components to integrate various artificial intelligence technologies, which is convenient to acquire revision knowledge from huge cases from multi-channels. At last, this article proposes how to explore the revision knowledge and characteristic adaptation methods, so we can improve the quality of recommendation and “support” the users effectively.
基于案例智能的个性化推荐系统
个性化需求的获取是有效推荐的关键。案例智能是人的感官、逻辑和创造力的综合表现。通过前面的案例,我们可以获得用户的偏好,这些偏好隐含在案例库中,推荐过程易于理解和接受。由于电子商务所处的环境复杂,案例作为案例智能系统知识表示的基础,可以采用半结构化或非结构化模型表示,甚至可以采用自然语言文本表示。提出了一种基于案例智能的个性化推荐系统。该系统具有良好的灵活性,采用模块化组件集成各种人工智能技术,便于从多渠道获取海量案例的修订知识。最后,本文提出了如何探索修改知识和特征适配方法,从而提高推荐质量,有效地“支持”用户。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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