Class Timing: Wednesday (14.00-15.30) and Thursday (15.40-17.10) at C405
Self-study Timing: Friday (16.30-17.30) at C405
Quiz: 2 September, 2025; Instructions; Syllabus: Lecture 1-5
Assignment: 9-19 October, 2025; Instructions; For part-time participants / students in interrnships: https://meet.google.com/sek-jrsg-rqz
Mid Sem Examination: 3.00 PM - 4.30 PM, 24 September, 2025; Solutions; Syllabus: Lecture 1-9
End Sem Examination: November, 2025; Solutions; Syllabus:
Format: Q1: 5 questions of 2 marks; Q2: 5 questions of 3 marks; Q3: 5 questions of 5 marks
3-0-0-4-4
Brief introduction to the field of Information Retrieval (IR).
Explanation of the importance of IR in various domains, including search engines, digital libraries, and data mining.
Lecture 1: Overview; Foundations of Information Retrieval; Source: CS54701 Information Retrieval by Clifton
Lecture 2: Indexing and Querying; Boolean Retrieval; Source: Chapter 1 & 2, Manning, Raghavan and Schütze
Lecture 3: Text Encoding; Source: Chapter 2, Manning, Raghavan and Schütze
Lecture 4: Dictionaries and Tolerant Retrieval; Source: Chapter 3, Manning, Raghavan and Schütze
Lecture 5: Index Construction; Source: Chapter 4, Manning, Raghavan and Schütze
Lecture 6: Index Compression; Source: Chapter 5, Manning, Raghavan and Schütze
Lecture 7: Scoring, Term weighting; Vector Space Model; Source: Chapter 6, Manning, Raghavan and Schütze
Lecture 8: Computing Scores; Source: Chapter 7, Manning, Raghavan and Schütze
Lecture 9: Evaluation in Information Retrieval; Source: Chapter 8, Manning, Raghavan and Schütze
Lecture 10: Relevance Feedback and Query Expansion; Source: Chapter 9, Manning, Raghavan and Schütze
Lecture 11: XML Retrieval; Source: Chapter 10, Manning, Raghavan and Schütze
Lecture 12: Probabilistic Information Retrieval; Source: Chapter 11, Manning, Raghavan and Schütze
Lecture 13: Language Models; Source: Chapter 12, Manning, Raghavan and Schütze
Self-Study 1: Web Crawling
Self-Study 2: Indexing and Searching using pySolr
Self-Study 3: Boolean Retrieval using Python
Self-Study 4: Vector Space Retrieval using Python
Self-Study 5: Probabilistic Retrieval using Python
Self-Study 6: Classification in Retrieval using Python
Midsem
Lecture 14: Text Classification; Source: Chapter 13, Manning, Raghavan and Schütze
Lecture 15: Distributed Representations; Source: Chapter 14, Manning, Raghavan and Schütze
Lecture 16: Learning Ranking; Source: Chapter 15, Manning, Raghavan and Schütze
Lecture 17: ?; Source: Chapter ?, Manning, Raghavan and Schütze
Lecture 18: ?; Source: Chapter ?, Manning, Raghavan and Schütze
Lecture 19: ?; Source: Chapter ?, Manning, Raghavan and Schütze
Lecture 20: ?; Source: Chapter ?, Manning, Raghavan and Schütze
Endsem
Introduction to Information Retrieval, by C. Manning, P. Raghavan, and H. Schütze (Cambridge University Press, 2008).
Search Engines: Information Retrieval in Practice. Croft, W. Bruce; Metzler, Donald; Strohman, Trevor. Addison Wesley (2008)
Information Retrieval: Implementing and Evaluating Search Engines, Stefan Buettcher, Charles L. A. Clarke, Gordon V. Cormack. MIT Press. (2010)
Modern Information Retrieval, Ricardo Baeza-Yates and Berthier Ribeiro-Neto, Addison-Wesley, (1999)
Quiz (10%), Assignment 1 (20%), Midterm (10%), Assignment 2 (20%), Assignment 3 (20%), Endterm (20%)