Course
code CS475
credit_hours 3
title Information Retrieval
arbic title
prequisites CS212, BA304
credit hours 3
Description/Outcomes This course studies the theory, design, and implementation of text-based information systems. The Information Retrieval core components of the course include statistical characteristics of text, representation of information needs and documents, several important retrieval models (boolean, vector space, probabilistic, inference net, and language modeling), clustering algorithms, collaborative filtering, automatic text categorization, and experimental evaluation. The software architecture components include design and implementation of high-capacity text retrieval and text filtering systems. It also introduces web search including crawling, link-based algorithms, and Web metadata text/Web clustering, classification text mining.
arabic Description/Outcomes
objectives 1. Identify basic IR models.
2. Understand basic tokenizing, indexing, and implementation of Vector-Space Retrieval.
3. Use query operations and languages.
4. Apply experimental evaluation of IR.
5. Differentiate categorization algorithms: Rocchio, nearest neighbor, and naive Bayes.
6. Use naive Bayes text classification for ad hoc retrieval.
7. Identify clustering algorithms: agglomerative clustering k-means expectation maximization (EM).
8. Learn information extraction and integration.
arabic objectives
ref. books Chakrabarti S., Mining the Web: Discovering Knowledge from Hypertext Data, Morgan-Kaufmann.
arabic ref. books
textbook Croft B., Metzler D., and Strohman T., Search Engines: Information Retrieval in Practice, Addison-Wesley.
arabic textbook
objective set
content set
course file 4_CS475_CS475 - Information Retrival.pdf
Course Content
content serial Description