Framework to Mine XML Format Event Logs

Q3 Computer Science

International Journal of Advances in Soft Computing and its Applications Pub Date : 2022-11-28 DOI:10.15849/ijasca.221128.07

A. Sheng, J. Jamil, I. Shaharanee

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引用次数: 0

Abstract

Abstract A lot of applications including event logs and web pages uses XML format for utilizing, keeping, transferring and displaying data. Thus, volume of data expressed in XML has increase rapidly. Numerous research has been done to extract and mine information from XML documents. Mining XML documents allows an understanding to the architecture and composition of XML documents. Generally, frequent subtree mining is one of the methods to mine XML documents. Frequent subtree mining searches the relation between data in a tree structured database. Due to the architecture and the composition of XML format, normal data mining and statistical analysis difficult to be performed. This paper suggests a framework that flattens and converts tree structured data into structured data, while maintaining the information of architecture and the composition of XML format. To gain more information from event logs, converting into structured data from semistructured format grants more ability to perform variety data mining techniques and statistical test. Keywords: Flatten Sequential Structure Model, XML Format Event Logs, Data Mining, Statistical Analysis.

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挖掘XML格式事件日志的框架

摘要包括事件日志和网页在内的许多应用程序都使用XML格式来利用、保存、传输和显示数据。因此，用XML表示的数据量迅速增加。已经进行了大量的研究来从XML文档中提取和挖掘信息。挖掘XML文档可以理解XML文档的体系结构和组成。通常，频繁子树挖掘是挖掘XML文档的方法之一。频繁的子树挖掘在树结构数据库中搜索数据之间的关系。由于XML格式的体系结构和组成，很难进行正常的数据挖掘和统计分析。本文提出了一种将树结构数据扁平化并转换为结构化数据的框架，同时保留了体系结构信息和XML格式的组成。为了从事件日志中获得更多信息，将半结构化格式转换为结构化数据可以增强执行各种数据挖掘技术和统计测试的能力。关键词：展平序列结构模型，XML格式事件日志，数据挖掘，统计分析。

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来源期刊

International Journal of Advances in Soft Computing and its Applications Computer Science-Computer Science Applications

CiteScore

3.30

自引率

0.00%

发文量

期刊介绍： The aim of this journal is to provide a lively forum for the communication of original research papers and timely review articles on Advances in Soft Computing and Its Applications. IJASCA will publish only articles of the highest quality. Submissions will be evaluated on their originality and significance. IJASCA invites submissions in all areas of Soft Computing and Its Applications. The scope of the journal includes, but is not limited to: √ Soft Computing Fundamental and Optimization √ Soft Computing for Big Data Era √ GPU Computing for Machine Learning √ Soft Computing Modeling for Perception and Spiritual Intelligence √ Soft Computing and Agents Technology √ Soft Computing in Computer Graphics √ Soft Computing and Pattern Recognition √ Soft Computing in Biomimetic Pattern Recognition √ Data mining for Social Network Data √ Spatial Data Mining & Information Retrieval √ Intelligent Software Agent Systems and Architectures √ Advanced Soft Computing and Multi-Objective Evolutionary Computation √ Perception-Based Intelligent Decision Systems √ Spiritual-Based Intelligent Systems √ Soft Computing in Industry ApplicationsOther issues related to the Advances of Soft Computing in various applications.