Context-Aware News Recommender in Mobile Hybrid P2P Network

K. Yeung, Yanyan Yang, D. Ndzi
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引用次数: 13

Abstract

With the emergence of pervasive environment, mobile recommender needs to make use of user in-time contextual information to provide personalized recommendation. In this paper, a proactive context-aware news recommender in mobile hybrid P2P network is designed and implemented. We develop a general Analytic Hierarchy Process (AHP) model through empirical studies. We discuss how the relative weight of each AHP criteria can be computed via user assignment and user history. We combine both Contend-based filtering and Collaborative filtering approach to predict user interest using Bayesian Network. The experiments show the system can recommend real time news stories that satisfy the user.
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移动混合P2P网络中上下文感知的新闻推荐
随着普适环境的出现,移动推荐需要利用用户实时的语境信息提供个性化的推荐。本文设计并实现了一种基于移动混合P2P网络的主动上下文感知新闻推荐系统。通过实证研究,我们建立了一个通用的层次分析法模型。我们讨论了如何通过用户分配和用户历史计算每个AHP标准的相对权重。我们将基于内容的过滤和协同过滤相结合,利用贝叶斯网络预测用户兴趣。实验结果表明,该系统能够推荐用户满意的实时新闻报道。
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