Mining User Navigation Patterns from Web Access Log Files

Since the Web is the biggest and most widely known information source that is easily accessible and searchable, on the positive side, there is widespread participation in authoring content. Web consists of billions of interconnected documents (called Web pages) which are authored by millions of people. Web Mining aims to discover the informative knowledge or information from massive data sources available on the Web by using data mining or machine learning approaches. Web usage mining is one of the categories of Web mining which discovers user behavioral patterns from searches and accesses logs of user interactions with Websites. This book presents methods, approaches and techniques to perform three main tasks of Web usage mining that are called Preprocessing, Pattern Discovery, and Pattern Analysis. Another main part discussed in this book is Web server log file Analysis. Mainly this book is suitable for researchers who are interested in the techniques and applications of Web search, Web data management, Web mining and Web recommendation as well as Web usage mining for in-depth academic research and industrial development to gain rapid knowledge in related areas.