Information Retrieval
Instructor: Venkatesh Vinayakarao
Term: Aug - Sep 2019

Welcome to Information Retrieval (IR) course! It is difficult to imagine living without search engines. Availability of big data has necessitated a systematic study of retrieval techniques. Principles and practices of information retrieval have been a focus of both researchers and practitioners alike. This course is not about just search engines. It is about dealing with big data and retrieving information which opens up several interesting applications. This course will introduce students to key parts of IR such as indexing techniques, challenges in query processing and well-known retrieval models.

Key Learning Objectives

At the end of this course, you should be able to:
  • Understand and apply text indexing techniques to big data.
  • Understand and apply text ranking techniques.
  • Analyze and evaluate existing retrieval systems.

Lecture Resources

Lecture #TopicReadingsSlides/Material
1Introduction to Boolean RetrievalChapter 1 from CPSLecture1
2Overview of Indexing, Query Processing and EvaluationChapter 2 from CPSLecture2
3Storing Dictionaries and Tolerant RetrievalChapter 3 from CPSLecture3
4String Handling and Spelling CorrectionChapter 3 from CPSLecture4
Phonetic Correction [By Vinoothna]
5Index ConstructionChapter 4 from CPSLecture5
6Building Search Engines with SolrSolr WebsiteLecture6-Solr [By Suchitra]
7Dynamic and Distributed Indexing
Lucene Demo
Chapter 4 from CPSLecture7
Lucene Demo
8Index CompressionChapter 5 from CPSLecture8
9Vector Space ModelChapter 6,7 from CPSLecture9
10IR EvaluationChapter 8 of CPSLecture10
Zonal Indexing
11Probabilistic RetrievalChapter 11 of CPSLecture11
12Web Basics, Web Crawling, Link AnalysisChapter 19,20,21 of CPSLecture12
Langauge Models

InstrumentMax Marks
Final Exam60%
Assignments (3 * 10% each)30%
In-Class Quiz (5 * 2%)10%

Familiarity with Java will help in coding with Lucene. You may use your favourite programming language (for assignments) as long as the objectives of the assignment are met. Basic understanding of linear algebra, set theory and probability will be useful in understanding the IR models.


  • [CPS] An Introduction to Information Retrieval. Christopher D. Manning, Prabhakar Raghavan, Hinrich Schütze.
  • [BDT] Search Engines: Information Retrieval in Practice. Bruce Croft, Donald Metzler, Trevor Strohman

If you are not having fun, you are not the best student you can be!