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 retrieval techniques to big data.
  • Understand and apply text indexing techniques.
  • Analyze and evaluate existing retrieval systems.

Lecture Resources

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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
5Index Construction and Index CompressionChapter 4,5 from CPS
6,7Vector Space ModelChapter 6,7 from CPS
8,9IR EvaluationChapter 8 of CPS
10Relevance FeedbackChapter 9 of CPS
11Probabilistic RetrievalChapter 11 of CPS
12Language Models for IRChapter 12 of CPS
13,14Web Basics, Web Crawling, Link AnalysisChapter 19,20,21 of CPS
15,16Advanced Topics IEntity Retrieval, Learning to Rank
...Advanced Topics II (if time permits)QA Systems, Knowledge Graphs, Eye Tracking, User Studies 


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

Pre-requisites
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.

Resources

Text
  • [CPS] An Introduction to Information Retrieval. Christopher D. Manning, Prabhakar Raghavan, Hinrich Schütze.
Reference
  • [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!