40324 Modern Information Retrieval

Hamid Beigy, Sharif University of Technology, Spring 2025.

Course Description

Information retrieval is the process through which a computer system can respond to a user's query for text-based information on a specific topic. Information retrieval was one of the first and remains one of the most important problems in the domain of natural language processing. Web search is the application of information retrieval techniques to the largest corpus of text anywhere and it is the area in which most people interact with information retrieval systems most frequently. In this course, we will cover basic and advanced techniques for building text-based information systems, including efficient text indexing, Boolean and vector-space retrieval models, evaluation and interface, issues, information retrieval techniques for the web, including crawling, link-based algorithms, and metadata usage, document clustering and classification, traditional and machine learning-based ranking approaches, questiona and answering systems, and recommender systems.

Course Information

Instructor: Hamid Beigy
Teaching Assistant: Reza Tavakoli
Time and Location: Saturday/Monday: 9:00 am - 10:30 am, CE 201, virtual class

Required Texts

[MRS] Christopher D. Manning and Prabhakar Raghavan, and Hinrich Schutze, Introduction to Information Retrieval, Cambridge University Press, 2008.
[HNG] Hang Li, Learning to Rank for Information Retrieval and Natural Language Processing, Morgan & Claypool, 2011.
[MC] Bhaskar Mitra and Nick Craswell, An Introduction to Neural Information Retrieval, Foundations and Trends in Information Retrieval, Vol. 13, No. 1, pp. 1-126, 2018.

Grading Policy

25%: Mid-term exam (1404/01/30).
30%: Final exam
35%: Homeworks.
15%: Quiz.

Lecture Schedule

Lecture	Lecture Date	Topics	Related Readings and Links	Homeworks & Assignments	Quizes
1	1403-11-20	Introduction	Chapter 1 of MRS
2	1403-11-27	Boolean information retrieval and document preprocessing	Chapters 1 & 2 of MRS
3	1403-11-29	Dictionaries and tolerant retrieval	Chapter 3 of MRS
4	1403-12-04	Index Construction	Chapter 4 of MRS
5	1403-12-06	Index compression	Chapter 5 of MRS
6	1403-12-11	Vector space model	Chapter 6 of MRS
7	1403-12-13	Scores in a complete search system	Chapter 7 of MRS
8	1403-12-18	Evaluation in information retrieval	Chapter 8 of MRS
9 10	1403-12-20 1403-12-25	Relevance feedback and query expansion	Chapter 9 of MRS
11	1404-01-16	Probabilistic Information Retrieval	Chapter 11 of MRS
12	1404-01-18	Language Models for Information Retrieval	Chapter 12 of MRS
13 14	1404-01-23 1404-01-25	Probabilistic text classification Vector space text classification	Chapters 13-15 of MRS
15	1404-01-30	Mid-term exam
16	1404-02-01	Vector space text classification	Chapters 13-15 of MRS
17 18 19	1404-02-06 1404-02-08 1404-02-13	Text clustering	Chapters 16 & 17 of MRS
20	1404-09-15	Dimensionality reduction and feature selection	Chapter 13 of MRS
21	1404-09-20	Latent Semantic Indexing	Chapter 18 of MRS
22 23	1404-02-22 1404-02-27	Web cralwing and search	Chapters 19 & 20 of MRS
24	1404-02-29	Link Analysis	Chapter 21 of MRS
25 26	1404-03-03 1404-03-05	Neural information retrieval	MC
27	1404-03-10	Retreival Agmented Generation
28	1404-03-12	Some IR applications
	1404-03-28	Final exam	At 9:00