{"title":"Mining user browsing pattern based on representative set","authors":"Zhou Hongfang, Wang Peng","doi":"10.1109/ICCIAUTOM.2011.6183905","DOIUrl":null,"url":null,"abstract":"Web log contains large volume of user browsing information. How to mine user browsing patterns is an important research topic. On the analysis of the present algorithms for mining user interests, user-interest can be used for mining user browsing patterns. In order to cluster overlapping objects effectively, a new concept-Cut Plane is introduced. And for achieving reasonable and acceptable running speed, representative set is presented too. On all of these foundations, RSBUBP (Representative Set Based User Browsing Patterns) algorithm is proposed. Experiments showed that it was accurate and scalable. It's suitable for application in E-business, such as to optimize Web site or to design personalized service.","PeriodicalId":177039,"journal":{"name":"2011 2nd International Conference on Control, Instrumentation and Automation (ICCIA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 2nd International Conference on Control, Instrumentation and Automation (ICCIA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCIAUTOM.2011.6183905","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Web log contains large volume of user browsing information. How to mine user browsing patterns is an important research topic. On the analysis of the present algorithms for mining user interests, user-interest can be used for mining user browsing patterns. In order to cluster overlapping objects effectively, a new concept-Cut Plane is introduced. And for achieving reasonable and acceptable running speed, representative set is presented too. On all of these foundations, RSBUBP (Representative Set Based User Browsing Patterns) algorithm is proposed. Experiments showed that it was accurate and scalable. It's suitable for application in E-business, such as to optimize Web site or to design personalized service.
Web日志包含了大量的用户浏览信息。如何挖掘用户浏览模式是一个重要的研究课题。通过对现有用户兴趣挖掘算法的分析，发现用户兴趣可以用于挖掘用户浏览模式。为了有效地聚类重叠对象，引入了切平面的概念。为了达到合理的、可接受的运行速度，还提出了代表集。在此基础上，提出了基于用户浏览模式代表集(Representative Set Based User Browsing Patterns, RSBUBP)算法。实验表明，该方法具有较好的准确性和可扩展性。它适用于电子商务中的应用，如优化网站或设计个性化服务。
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