CS 525/DS 595: Information Retrieval & Social Web
Wednesday 6:00pm - 8:50pm, Fuller Labs (FL) 311
Instructor: Kyumin Lee
Office Hours: Tuesday 9:30am - 10:30am and Wednesday 4:00pm - 5:00pm, FL 130
Email: kmlee (at) wpi.edu
Teaching Assistants: Ben Vo and Thanh Tran
Ben's Office Hours: Monday 1:00 pm ~ 2:00 pm, FL 316
Ben's email: vknguyen09 (at) gmail.com
Thanh's Office Hours: Friday 1:00 pm ~ 2:00 pm, FL 316
Thanh's email: thanhtd.ithut (at) gmail.com
Grader: Meng Wang
Meng's email: mwang2 (at) wpi.edu
This course introduces theory, design, and implementation of text-based and Web-based information retrieval systems. Students learn components and operation of search engines providing search services. Components include web crawlers, indexers, link-based ranking algorithms, and recommender systems.
By the end of the semester students will be able to:
- Understand the key concepts and models relevant to information storage and retrieval, including efficient text indexing, vector space model, Web search.
- Design, implement, and evaluate the core algorithms underlying a fully functional IR system, including the indexing, retrieval, and ranking components.
- Identify the salient features and apply recent research results in information storage and retrieval, including topics such as adversarial information retrieval, and social information management.
We are going to use Google Groups for all course communication. Join our Google Group. If you have a question to discuss with everyone, please post it to the group! If you have found a cool link to share with classmates, share it to the group. We will monitor the group and provide feedback. But everyone is encouraged to contribute.
I expect all students to have had some previous exposure to basic probability, statistics, algorithms, and data structures. You should be able to design and develop large programs and learn new software libraries on your own.
Primary Textbook is
Additional course readings will be drawn from the following textbook:
The detailed information regarding the grading is described in the syllabus.
- Attendance and in-class discussion 5%
- Assignments 24%
- Midterm 20%
- Final 20%
- Project 31%