Information Retrieval
Instructor: Venkatesh Vinayakarao
Term: Aug - Dec 2018
Teaching Assistants: To be announced.



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 interesting applications for information technology. 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.

Slides

Lecture 1 - Boolean Retrieval
Assignment 1: Deadline Passed.
Lecture 2 - Index Construction and Evaluation
Assignment 2: To be announced.

Topics

Part 1: Content Processing and Indexing
Boolean Retrieval, Content Processing - Tokeniation, Lemmatization, Stop Words, Stemming, Normalization, Indexing - Index Construction, Index Compression - Zipf's law, Heap's Law, Posting Lists.

Part 2: Relevance and Retrieval Models
Term Weighting - TF-IDF, Vector Space Model, TF-IDF Variants.

Part 3: Evaluating and Improving Retrieval Systems
Evaluation, Relevance Feedback, Query Expansion.

Evaluation
Note that depending on the number of student registrations, the number of assignments, score distribution for assignments and project might change.
InstrumentMax Marks
Midterm 120%
Midterm 220%
Final Exam30%
Assignment 12%
Assignments 2, 3 (4% each)8%
Project20%

Pre-requisites
Students must bring strong programming skills, preferrably in Java.

Project
The project component is mandatory. Students may form groups of up to three. The objective is to learn by building a search engine yourself. Project will be evaluated in three parts:
  • A two page technical report covering the approach.
  • A live demo of the project.
  • A 15 minute presentation.
Resources

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