LOGML: Log markup language for web usage mining. Web Usage Mining refers to the discovery of interesting information from user navigational behavior as stored in web access logs. While extracting simple information from web logs is easy, mining complex structural information is very challenging. Data cleaning and preparation constitute a very significant effort before mining can even be applied. We propose two new XML applications, XGMML and LOGML to help us in this task. XGMML is a graph description language and LOGML is a web-log report description language. We generate a web graph in XGMML format for a web site using the web robot of the WWWPal system. We generate web-log reports in LOGML format for a web site from web log files and the web graph. We further illustrate the usefulness of LOGML in web usage mining; we show the simplicity with which mining algorithms (for extracting increasingly complex frequent patterns) can be specified and implemented efficiently using LOGML

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References in zbMATH (referenced in 3 articles , 1 standard article )

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  1. Bifet, Albert: Adaptive stream mining: Pattern learning and mining from evolving data streams. (2010)
  2. Zaki, Mohammed J.; Aggarwal, Charu C.: XRules: An effective algorithm for structural classification of XML data (2006) ioport
  3. Punin, John R.; Krishnamoorthy, Mukkai S.; Zaki, Mohammed J.: LOGML: Log markup language for web usage mining (2002)