Forecasting and enhancing universities navigation outline procedure from web log data

A. Sivakumaran, P. Marikkannu
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Abstract

Web mining (WM) is the programmed disclosure of client access design from web servers. Universities gather vast volumes of data in their day by day operations, produced naturally by web servers and gathered in server access logs. The research shows the forecasting and enhancing universities navigation from web log data (F&E-UN-WLD). In the primary stage, F&E-UN-WLD concentrates on isolating the potential clients in web log data (WLD). Trial comes about speak about methodology can enhance the quality of grouping for client route design in web utilisation mining frameworks. These outcomes can be utilised for foreseeing client's next solicitation in the tremendous web destinations.
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利用网络日志数据预测和改进高校导航大纲程序
Web挖掘(Web mining, WM)是对Web服务器的客户端访问设计的程序化披露。大学在日常操作中收集大量数据,这些数据自然是由网络服务器产生的,并收集在服务器访问日志中。研究表明,利用网络日志数据(F&E-UN-WLD)对高校导航进行预测和改进。在初始阶段,F&E-UN-WLD专注于隔离web日志数据(WLD)中的潜在客户端。本文论述了在web利用挖掘框架中提高客户端路由设计分组质量的方法。这些结果可以用来预测客户的下一个请求在巨大的网络目的地。
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