Web Usage Mining: Pattern Discovery and Forecasting
This work addresses web usage mining for analyzing user interactions on a specific college website, but it appears incremental as it applies existing methods to new data without major innovations.
The paper tackled the problem of discovering user behavior patterns from college web log files and forecasting future access statistics, resulting in clusters representing frequently accessed patterns by visitor groups and predictions of visitor and hit counts.
Web usage mining: automatic discovery of patterns in clickstreams and associated data collected or generated as a result of user interactions with one or more Web sites. This paper describes web usage mining for our college log files to analyze the behavioral patterns and profiles of users interacting with a Web site. The discovered patterns are represented as clusters that are frequently accessed by groups of visitors with common interests. In this paper, the visitors and hits were forecasted to predict the further access statistics.