Towards Web Performance Mining

Web Mining is the application of data mining to discover useful knowledge from the Web. Web mining focuses now on four main research directions related to the categories of Web data: Web content mining, Web usage mining, Web structure mining, and Web user profile mining. Web content mining discovers what Web pages are about and reveals new knowledge from them. Web usage mining concerns the identification of patterns in user navigation through Web pages and is performed for the reasons of service personalization, system improvement, and usage characterization. Web structure mining investigates how the Web documents are structured, and discovers the model underlying the link structures of WWW. Web user profile mining discovers user’s profiles based on users’ behavior on the Web. We present the application of data mining in Web performance analysis. We call our approach Web performance mining (WPM). It has been defined to characterize the performance from the perspective of Web clients in the sense of the data transfer throughput in Web transactions. WPM adds a new dimension in Web mining research that focuses on using data mining techniques to analyze Web performance measurements to find interesting patterns in order to support decision-making in the use of Web, for example, to predict future state of good or poor performance in the access to particular Web servers. WPM is based on the measurements which are planned and performed using specific measurement tools and platforms. We developed the multi-agent distributed system MWING to support required active measurements.

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