一种集成用户画像与内容的服务重定向方法

发布时间：2018-05-14 18:44

本文选题：分布式服务框架 + 服务重定向　；参考：《小型微型计算机系统》2017年12期

【摘要】：随着互联网的发展,网站应用的规模正不断扩大,常规的垂直应用架构已慢慢无法应对这样的场景,而应用的大规模服务化则应运而生.大规模服务框架通常会建立一个服务注册中心,动态的注册和发现服务,使服务的位置透明.消费方通过获取服务提供方的地址列表,实现软负载均衡和Failover.而随着服务的累积,在候选服务集合越来越大的情况下,加快重定向的响应速度是其中的一个关键问题.本文旨在通过cookies跨域采集用户行为信息并对用户分群画像,用LDA分析网页内容并建立主题模型,进而提出一种基于用户画像与内容的服务重定向方法.该方法基于人群特征与内容修剪候选服务,可以大大减少搜索空间,降低计算量,以提高响应速度.实验结果验证了本文方法的有效性.
[Abstract]:With the development of the Internet, the scale of website application is expanding. The conventional vertical application architecture has been unable to cope with this kind of scenario, and the large-scale service of application has come into being. Large-scale service frameworks usually establish a service registry to dynamically register and discover services, making the location of services transparent. The consumer achieves soft load balancing and failure over by obtaining the address list of the service provider. With the accumulation of service, it is a key problem to accelerate the response speed of redirect when the candidate service set becomes larger and larger. The purpose of this paper is to collect user behavior information through cookies across domains, divide users into groups, analyze web content with LDA and set up theme model, and then propose a service redirection method based on user portrait and content. Based on crowd feature and content pruning candidate services, this method can greatly reduce the search space, reduce the amount of computation, and improve the response speed. The experimental results show that the proposed method is effective.
【作者单位】：湖北文理学院;武汉大学国际软件学院;
【基金】：国家重点研发计划项目(2016YFB0800400)资助国家自然科学基金项目(61572371)资助湖北省自然科学基金面上项目(2016CFB406)资助湖北文理学院教师科研能力培育基金项目(2016ZK004)资助
【分类号】：TP393.092

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