Bamshad Mobasher
Email: mobasher@cs.depaul.edu
Office: Loop Campus, CTI Building, Room 833
Phone: (312) 362-5174
Office Hours: Mondays. 4:00-5:30 (or by appointment)

Web mining refers to the automatic discovery of interesting and useful patterns from the data associated with the usage, content, and the linkage structure of Web resources. It has quickly become one of the most popular areas in computing and information systems because of its direct applications in e-commerce, e-CRM, Web analytics, information retrieval/filtering, Web personalization, and recommender systems. Employees knowledgeable about Web mining techniques and their applications are highly sought by major Web companies such as Google, Amazon, Yahoo, MSN and others who need to understand user behavior and utilize discovered patterns from terabytes of user profile data to design more intelligent applications. The primary focus of this course is on Web usage mining and its applications to e-commerce and business intelligence. Specifically, we will consider techniques from machine learning, data mining, text mining, and databases to extract useful knowledge from Web data which could be used for site management, automatic personalization, recommendation, and user profiling. The first half of the course will be focused on a detailed overview of the data mining process and techniques, specifically those that are most relevant to Web mining. The second half will concentrate on the applications of these techniques to Web and e-commerce data, and their use in Web analytics, user profiling and personalization. This course also counts as an advanced course for Computer Science students concentrating in AI or Data Analysis.

Assignments = 65%
Final Project = 35%
 

There will be 4-5 assignments during the quarter involving the concepts and techniques discussed in class. The assignments may involve experimenting with various tools, as well as other written or problem-oriented exercises. These assignments must be done individually. Late assignments will be penalized 10% per day (with weekends counting as one day).

For the class project, students can choose to do an implementation project, a data analysis project, or a research paper. Implementation projects may be done individually or in groups of 2 people (depending the complexity and the type of the project). Research papers and data analysis projects must be done individually. Each group or individual will submit a specific project proposal to be approved. More details about the possible project options, as well as due dates for the proposal and the final submission, are available in the Project section.

The following issues and topics will be covered throughout the course. Many of these topics will be revisited several times during the course in a variety of contexts.