The exponential growth of the Web in terms of Web sites and their users during the past decade has generated huge amount of data related to the user's interactions with the Web sites. This data is recorded in the Web access log files of Web servers and usually referred as Web Usage Data (WUD). Knowledge Discovery from Web Usage Data (KDWUD) is that area of Web mining which deals with the application of data mining techniques to extract interesting knowledge from the WUD. As Web sites continue to grow in size and complexity, the results of KDWUD have become very critical for efficient and effective management of the activities related to e- business, e-education, e-commerce, personalization, Web site design and management, network traffic analysis, the cache, the proxies, great diversity of Web pages in a site, search engine's complexity, and to predict user's actions. Nevertheless, understanding the needs of their users is vital for the owners of the Web sites in order to serve them better. This book covers three main stages of knowledge discovery – Preprocessing of raw WUD, Pattern Discovery and Pattern Analysis.