Web usage mining tool by integrating sequential pattern mining with graph theory

V. Musale, D. Chaudhari
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引用次数: 2

Abstract

In this era, the web usage mining plays one of the important role in analyzing and improving performance of web applications. Initially in this paper, the concept of web usage mining has been introduced along with Improved AprioriAll algorithm which is the base algorithm for the proposed tool along with its limitation. The improved approach is discussed which integrates sequential pattern mining with graph theory. In the next part, design of web usage mining tool with improved approach is discussed. Implementation details of the tool are discussed along with the results. The last part covers how the raw result from the proposed tool can be further visualized and analyzed using new technologies like D3.js and Neo4j. The future scope of the proposed tool is mentioned at the end of the paper.
将顺序模式挖掘与图论相结合的Web使用挖掘工具
在这个时代,web使用挖掘是分析和提高web应用性能的重要手段之一。本文首先介绍了web使用挖掘的概念,以及改进的AprioriAll算法,该算法是所提出工具的基础算法,以及它的局限性。讨论了将序列模式挖掘与图论相结合的改进方法。接下来,讨论了基于改进方法的web使用挖掘工具的设计。讨论了该工具的实现细节以及结果。最后一部分介绍了如何使用D3.js和Neo4j等新技术进一步可视化和分析该工具的原始结果。在论文的最后提到了所提出的工具的未来范围。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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