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

机译:一种使用KHM和FP增长进行用户导航模式预测的新型混合技术

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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:网络上有大量数据可用。一些用户倾向于访问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混合方法。本文讨论的方法正在实施中,并且使用两个不同的数据集对结果进行分析并与其他相关系统进行比较。还比较了有关执行时间,准确性和频繁模式数量的结果。

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