Mining of Social, Professional and Web Networks
CSE 450: Spring 2010 Syllabus

Course Web page
The course Web page is Announcements, assignments, and some lecture materials will be posted on the corresponding CourseInfo (Moodle) site.
The course will be taught by Prof. Brian D. Davison and Prof. Roger N. Nagel.

Prof. Davison's homepage is His office is in Packard 380, and office hours and contact information are posted on his home page. All other meetings should be by appointment.

Prof. Nagel's homepage is His office is Packard 254D.

Class meetings will be held Wed 4:10-6:50 in Maginnes 103.
No required texts. Recommended: Reshaping Your Business with Web 2.0, by Casarez, Cripe, Sini, and Weckerle (McGraw-Hill, 2009); Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data, by Bing Liu (Springer, 2007); and Data Mining: Practical Machine Learning Tools and Techniques, 2nd Ed, by Witten and Frank (Morgan Kaufmann, 2005).

Reading List
A schedule of topics and papers to read will be published on the course website.

CSE345/445 WWW Search Engines or CSE430 Textual Data Mining or CSE 347/447 Data Mining or CSE326/426 Pattern Recognition or permission of the instructor.
Expected Work
Attendance is required. Coursework will primarily consist of paper critiques and presentations along with a semester-long network mining project (from which results will be presented to the class and in a technical report).
Grading Components
Grades will be determined through a combination of class participation, presentation quality and preparedness, paper critiques, and course project. (Percentages still to be determined.)

A late project or homework will be docked 10% of its total value for each 24 hour period for which it is late. No work will be accepted more than five days late, nor for assignments for which a solution has been posted or presented in class.

Topics to be Covered
  • Reading and critiquing technical publications
  • Mining of Social Networks
  • Mining of Professional Networks
  • Mining of Web Networks
  • Policy on Academic Integrity and Collaboration
    All work, unless explicitly stated in the problem definition, is to be an individual effort. You are encouraged to discuss assignments with one another, your friends, and with the instructors and graders of the course. Indeed, this may be the most effective method of learning. You may share concepts, approaches and strategies for producing a solution. However all work submitted in your name must be your own. If necessary, violations will be considered as cases of academic dishonesty.
    Policy on Disabilities
    If you have a disability for which you are or may be requesting accommodations, please contact both your instructor and the Office of Academic Support Services, University Center C212 (610-758-4152) as early as possible in the semester. You must have documentation from the Academic Support Services office before accommodations can be granted.
    Other Relevant University Policies
  • Religious Holidays
  • Lehigh Computer Usage
  • Academic Integrity

  • This page is
    Last revised: 19 January 2010, Prof. Davison.