{"title":"Web信息检索系统中一种有效的加权算法","authors":"R. Agarwal, K. Arya, S. Shekhar, Rakesh Kumar","doi":"10.1109/CICN.2011.25","DOIUrl":null,"url":null,"abstract":"Web Usage mining, also known as Web Log mining, is an application of data mining algorithms to Web access logs to find trends and regularities in Web users' traversal patterns. The results of Web Usage Mining have been used in improving Web site design, business and marketing decision support, user profiling, and Web server system performance. Web page prediction technique is a very important research area in web technologies. Mining is useful for web path traversal pattern from web logs. This paper presents an efficient algorithm for web page prediction from large web logs visited by a user. We assign a significant weight to each page based on time spent by user on each page, visiting frequency and click event done on each page.","PeriodicalId":292190,"journal":{"name":"2011 International Conference on Computational Intelligence and Communication Networks","volume":"195 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":"{\"title\":\"An Efficient Weighted Algorithm for Web Information Retrieval System\",\"authors\":\"R. Agarwal, K. Arya, S. Shekhar, Rakesh Kumar\",\"doi\":\"10.1109/CICN.2011.25\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Web Usage mining, also known as Web Log mining, is an application of data mining algorithms to Web access logs to find trends and regularities in Web users' traversal patterns. The results of Web Usage Mining have been used in improving Web site design, business and marketing decision support, user profiling, and Web server system performance. Web page prediction technique is a very important research area in web technologies. Mining is useful for web path traversal pattern from web logs. This paper presents an efficient algorithm for web page prediction from large web logs visited by a user. We assign a significant weight to each page based on time spent by user on each page, visiting frequency and click event done on each page.\",\"PeriodicalId\":292190,\"journal\":{\"name\":\"2011 International Conference on Computational Intelligence and Communication Networks\",\"volume\":\"195 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-10-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"15\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 International Conference on Computational Intelligence and Communication Networks\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CICN.2011.25\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 International Conference on Computational Intelligence and Communication Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CICN.2011.25","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 15
摘要
Web Usage mining,又称Web Log mining,是将数据挖掘算法应用到Web访问日志中,以发现Web用户遍历模式的趋势和规律。Web Usage Mining的结果已用于改进Web站点设计、业务和营销决策支持、用户分析和Web服务器系统性能。网页预测技术是Web技术中一个非常重要的研究领域。从web日志中挖掘web路径遍历模式是非常有用的。本文提出了一种从用户访问的大量网页日志中进行网页预测的有效算法。我们根据用户在每个页面上花费的时间、访问频率和在每个页面上完成的点击事件为每个页面分配重要的权重。
An Efficient Weighted Algorithm for Web Information Retrieval System
Web Usage mining, also known as Web Log mining, is an application of data mining algorithms to Web access logs to find trends and regularities in Web users' traversal patterns. The results of Web Usage Mining have been used in improving Web site design, business and marketing decision support, user profiling, and Web server system performance. Web page prediction technique is a very important research area in web technologies. Mining is useful for web path traversal pattern from web logs. This paper presents an efficient algorithm for web page prediction from large web logs visited by a user. We assign a significant weight to each page based on time spent by user on each page, visiting frequency and click event done on each page.