A Data Warehousing and Data Mining Framework for Web Usage Management

Abstract

A new challenge in Web usage analysis is how to manage and discover informative patterns from various types of Web data stored in structured or unstructured databases for system monitoring and decision making. In this paper, a novel integrated data warehousing and data mining framework for Website management and patterns discovery is introduced to analyze Web user behavior. The merit of the framework is that it combines multidimensional Web databases to support online analytical processing for improving Web services. Based on the model, we propose some statistical indexes and practical solutions to intelligently discover interesting user access patterns for Website optimization, Web personalization and recommendation etc. We use the Web data from a sports Website as data sources to evaluate the effectiveness of the model. The results show that this integrated data warehousing and mining model is effective and efficient to apply into practical Web applications.