40324 Modern Information Retrieval

Hamid Beigy, Sharif University of Technology, Fall 2023.

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 Assistants: Amir Moeini, Amin Davoodabadi, Mohammad Mahdi Abootorabi, Arshia Dadras, Sara Azarnoush, Bardia Mohammadi, Ali Nazari, Alireza Heidari, Amir Mohammad Fakhimi, Armin Saghafian, Mohammad Abolnejadian, Nona Ghazizadeh, Kian Omoomi, Roya Ghavami, Abolfazl Malekahmadi, Mohammadreza Daviran, Mohammad Moshtaghifar, Kian Shamsaie
Time and Location: Saturday/Monday: 9:00 am - 10:30 am, CE 101, 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 (1402/08/13).
25%: Final exam (1402/11/02).
35%: Homeworks.
15%: Quiz.

Lecture Schedule

Lecture	Lecture Date	Topics	Related Readings and Links	Homeworks & Assignments	Quizes
1	1402-07-03	Introduction	Chapter 1 of MRS
2 3	1402-07-08 1402-07-10	Boolean information retrieval and document preprocessing	Chapters 1 & 2 of MRS
4	1402-07-15	Dictionaries and tolerant retrieval	Chapter 3 of MRS
5	1402-07-17	Index Construction	Chapter 4 of MRS
6	1402-07-22	Index compression	Chapter 5 of MRS
7	1402-07-24	Vector space model	Chapter 6 of MRS	HW1 release	Quiz 1
8	1402-07-29	Scores in a complete search system	Chapter 7 of MRS
9	1402-08-01	Evaluation in information retrieval	Chapter 8 of MRS
10	1402-08-06	Relevance feedback and query expansion	Chapter 9 of MRS
11	1402-08-08	Probabilistic Information Retrieval	Chapter 11 of MRS		Quiz 2
12	1402-08-13	Mid-term exam
13	1402-08-15	Language Models for Information Retrieval	Chapter 12 of MRS	HW 1 deadline & HW 2 release
14 15 16 17	1402-08-20 1402-08-22 1402-08-27 1402-08-29	Probabilistic text classification Vector space text classification	Chapters 13-15 of MRS
18 19 20	1402-09-04 1402-09-06 1402-09-11	Text clustering	Chapters 16 & 17 of MRS	– – HW 2 deadline & HW 3 release	Quiz 3 – –
21	1402-09-13	Dimensionality reduction and feature selection	Chapter 13 of MRS
22	1402-09-18	Learning to rank	Chapters 1-3 of HNG
23	1402-09-20	Latent Semantic Indexing	Chapter 18 of MRS
24 25	1402-09-25 1402-09-27	Web cralwing and search	Chapters 19 & 20 of MRS
26	1402-10-02	Link Analysis	Chapter 21 of MRS	HW 3 deadline & HW 4 release	Quiz 4
27 28 29	1402-10-04 1402-10-09 1402-10-11	Neural information retrieval Some other related topics	MC
	1402-10-23			HW 4 deadline
	1402-11-02	Final exam	At 9:00