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A novel hybrid technique for user navigation pattern prediction using KHM and FP growth

机译:一种新型混合技术,用于使用KHM和FP增长的用户导航模式预测

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A huge amount of data is available on the web. Several users tend to access the data available on the internet. This makes it difficult to understand the browsing behavior of the user. The browsing history of the user is recorded in the web server log files. Such log files need to be analyzed. The approach described in this paper is based on a novel hybrid technique for analyzing the browsing patterns. It involves a novel and hybrid approach based on clustering and pattern mining algorithm. The approach discussed in this paper is being implemented and the results are analyzed and compared with other related system using two different datasets. The results are also compared concerning the execution time, accuracy and number of frequent patterns.
机译:Web上有大量数据。有几个用户倾向于访问Internet上可用的数据。这使得难以理解用户的浏览行为。用户的浏览历史记录在Web服务器日志文件中。需要分析此类日志文件。本文描述的方法基于一种用于分析浏览模式的新型混合技术。它涉及一种基于聚类和模式挖掘算法的新颖和混合方法。在本文中讨论的方法正在实施,并将结果与​​使用两个不同的数据集进行分析并与其他相关系统进行比较。还比较执行时间,准确性和频繁模式的准确性和数量的结果。

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