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Obtaining subject data from log files using deep log analysis: case study OhioLINK

机译:使用深度日志分析从日志文件中获取主题数据:案例研究OhioLINK

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Traditionally web site statistics and analysis focus on the organization and location information of Internet Protocol addresses and do not analyse sub-network and computer-label information. This paper aims to extract and make use of the information content of sub-network labels in transactional server log files and add an additional level to transaction log analysis. The authors apply microanalytical procedures (i.e. analysis of small segments and sections of log files) to the analysis of log files of the OhioLINK electronic journal service. The authors demonstrate an analysis based on extracted sub-network information and argue that these names can be interpreted as departmental (subject) names. They present an analysis between journal subject groupings and departments based on sub-network labels and find a degree of correlation between department name and subject of journal use. Further, the authors break down journal usage by sub-network label information. The analyses show that sub-network names reflect the physical location of the computer. This presents another possibility of analysing what journals are being used by which academic department.
机译:传统上,网站统计和分析着重于Internet协议地址的组织和位置信息,而不分析子网和计算机标签信息。本文旨在提取和利用事务服务器日志文件中子网标签的信息内容,并为事务日志分析增加新的层次。作者将微观分析程序(即,对日志文件的小片段和小部分进行分析)应用于OhioLINK电子期刊服务的日志文件分析。作者演示了基于提取的子网信息的分析,并认为这些名称可以解释为部门(主题)名称。他们基于子网标签对期刊主题分组和部门之间进行了分析,并找到了部门名称和期刊使用主题之间的相关程度。此外,作者还通过子网标签信息细分了期刊的使用情况。分析表明,子网名称反映了计算机的物理位置。这提供了分析哪个学术部门正在使用哪些期刊的另一种可能性。

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