Sie sind hier

Vorlesung Web Mining

Course Web Mining
Summer semester 2006/2007

 

 

Prof. Dr. Dr. Sergej Sizov

 

Organization - Themes

News

The results of the oral exam (Monday, 13 Aug 2007) are now available on WebCT (section Announcements).

 

 

Course Organization

  • Location: Monday 4 p.m. c.t. (i.e. 16.15) in A-213
  • The volume of this course is 2 academic hours per week.
  • Target audience: Computer Science, CV.
  • Recommended prerequisites: successful participation in the course "Database Systems" or "Information Retrieval", background knowledge of linear algebra, probability theory und stochastics. The course will offer major basics in these disciplines as they are crucial for several course themes. However, better understanding of the material may require self-study of recommended related work.
  • Examination: oral exam at the end of the summer semester
  • Course ID: 4.1.23

Contents

Web mining refers to the discovery of interesting and useful knowledge from the data associated with the usage, content, and the structure of Web resources. It has quickly become one of the most important areas in Computer and Information Sciences because of its direct applications in e-commerce, e-CRM, Web analytics, information retrieval/filtering, and Web information systems. 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 business intelligence, site management, personalization, and user profiling. The course will also provide a brief overview of other areas in Web mining, such as Web content mining and Web structure mining.

Course Material

Our course makes use of the WebCT platform to manage course material (slides, handouts), online discussions, announcements, and additional literature for further readings. The backup set of slides is also available on the course homepage.

To access course materials, you need to get a WebCT Account (the registration is fast and easy), and then to subscribe for the course using the course-specific code 406e320e and your WebCT-ID.