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Lecture |
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Information Retrieval A |
Enrollment Information (not real time - data refreshed nightly)
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Class #:
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17606 | |
Enrollment Capacity:
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15 |
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Section:
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A |
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Enrollment Total:
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0 |
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Credits:
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3.00 credits
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Seats Available:
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15 |
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Dates:
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08/28/2023 - 12/11/2023 |
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Status:
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OPEN |
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Days, Time:
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M W , 5:00 PM - 6:20 PM |
| Room: |
Nsc 216 |
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North Campus |
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| Enrollment Requirements |
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Prerequisites: Pre-Requisite: CSE 250, MTH 309; Approved Computer Science, Computer Engineering, Bioinformatics/CS Majors only. Students must complete a mandatory advisement session with their faculty advisor. |
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| Course Description |
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| 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. |
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| Instructor(s) |
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Srihari |
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| On-line Resources |
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| Other Courses Taught By: Srihari |
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