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Research on personalized information service on mobile networks based on mining user's interest

机译:基于采矿用户兴趣的移动网络个性化信息服务研究

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Personalized service is becoming a hot topic in information processing field. Meanwhile, mobile network operators pay much more attention to information service than they used to do. It is necessary to provide pertinent service to different customers if different users have different demands. To meet the need of personalized service system and aim to implementing personalized information recommendation, a new model on mobile networks is purposed at the beginning of this paper. Then the paper focuses on research on the relationship between users' behavior of using the system and their preference and discussing the interests reflected by those users' log files. The paper gives an algorithm of mining user's true preference on mobile network. Then the paper introduces a personalized information recommendation engine to implement recommending valuable information items to users. In this paper, some background of information service system on mobile networks is introduced firstly. Then a new model of this personalized service system is described. The association between user's data and their hidden preference as well as a concerned algorithm is discussed. Then, two important methods to implement personalized service, clustering and mining association rules, are depicted. An experiment to check the model and these algorithms is introduced and analyzed at the end of the paper.
机译:个性化服务正在成为信息处理领域的热门话题。与此同时,移动网络运营商比以前更多地关注信息服务。如果不同的用户有不同的需求,有必要为不同客户提供相关服务。为满足个性化服务系统的需求,并旨在实施个性化信息建议,在本文的开头时,移动网络上的新模型是用的。然后本文重点介绍了使用系统的用户行为与其偏好的关系,并讨论这些用户日志文件所反映的兴趣。本文给出了一种挖掘用户在移动网络上的真实偏好的算法。然后本文介绍了一个个性化信息推荐引擎,以实现向用户推荐有价值的信息项。本文首先介绍了移动网络上的信息服务系统的一些背景。然后,描述了该个性化服务系统的新模型。讨论了用户数据与隐藏偏好以及有关算法之间的关联。然后,描绘了实现个性化服务,聚类和挖掘关联规则的两个重要方法。在纸张结束时介绍并分析了检查模型和这些算法的实验。

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