Information Retrieval
This course will focus on text-based information retrieval (IR) techniques, more popularly known as search engines. Various IR models such as the Boolean model, vector space model, probabilistic model will be studied. Efficient indexing techniques for large document collections as well as specialized collections will be examined. Various query expansion techniques such as local context analysis will be introduced. Finally, the course will also discuss search engines for the web, and the use of link analysis to determine document/page relevance. Students will work on written assignments, as well as hands-on programming projects to gain expertise in this area.
None presently available.
CSE 250, MTH 309 MTH 309, CSE 250
| Semester | Section | Title | Instructor | Credit Hours | Enrolled |
|---|---|---|---|---|---|
| Fall 2013 | LR | Information Retrieval | Dr. Rohini K. Srihari | 4 | 0/ 5 |
| Fall 2011 | LR | Information Retrieval | Dr. Rohini K. Srihari | 4 | 4/ 5 |
| Fall 2010 | LR | Information Retrieval | Dr. Rohini K. Srihari | 4 | 4/10 |
| Fall 2009 | LEC | Information Retrieval | Dr. Rohini K. Srihari | 4 | 5/10 |
| Spring 2008 | LEC | Information Retrieval | Dr. Rohini K. Srihari | 4 | 0/ 3 |