Abstract:
Web Usage Mining (WUM) is the process of extracting knowledge from Web user’s access data by exploiting Data Mining techniques. It mines the secondary data (web logs) derived from the users' interaction with the web pages during certain period of Web sessions. In the present research work, a hybrid method is proposed, which uses the ant-based clustering and LCS classification methods to find and predict user’s navigation behaviour. The proposed system works in two phases, (i) the offline phase and (ii) the online phase. The offline phase takes care of preprocessing and clustering, while the classification and prediction is performed during the online phase. Ant-based clustering method used to discover or extract user’s navigational pattern from web log files. The LCS classification algorithm uses the knowledge from offline stage and predicts the users’ next request.
