Hours : 04 (theory) + 04 (laboratory, tutorials, presentations) per week
Course Objectives & Prerequisites:
The course aims
to introduce the paradigms and techniques of modern Information Retrieval (IR).
It focuses on the information retrieval from the World Wide Web (Web) and
describes algorithms, data structures and techniques for it.
The course is
designed as an introductory course in IR and as such only assumes that the
student opting for this elective course has successfully completed a basic
course in programming and understands fundamental concepts in Computer Networks
and the Web. A prior course in Data Structures and Artificial Intelligence and
hands-on JAVA/ Python/ R programming will help improve the pace of learning.
Information, Information Need and Relevance; The IR System; Early developments in IR, User Interfaces.
Retrieval and IR Models:
Boolean Retrieval; Term Vocabulary and Postings list; Index Construction; Ranked
and other alternative Retrieval Models.
Notion of Precision and Recall; Precision-Recall Curve, Standard Performance Measures such as MAP, Reciprocal ranks, F-measure, NDCG, Rank Correlation.
Representation; Vector Space Model; Feature Selection; Stop Words; Stemming; Notion of Document Similarity; Standard Datasets..
Classification and Clustering:
Notion of Supervised and Unsupervised Algorithms; Naive Bayes, Nearest Neighbour and Rochio’s algorithms for Text
Classification; Clustering Methods such as K-Means.
Applications/ Laboratory Exercises.
and Reference Books:
Baeza-Yaets and Berthier Ribeiro-Neto, Modern Information Retrieval: The Concept
and Technology behind Search, 2nd Edition, Addison-Wesley, 2011. [Companion
Website - contains certain downloadable chapters, slides and resources ]
P. Raghvan and H. Schutze, Introduction to Information Retrieval, Cambridge
University Press, 2008 [Companion
Website - contains downloadable book, slides and exercises]
David A. Grossman and Ophir Frieder, Information Retrieval: Algorithms and
Heuristics, 2nd Ed., Springer, 2008.
Buettcher, Charles L.A. Clarke and Gordon V. Carmack, Information Retrieval:
Implementing and Evaluating Search Engines, MIT Press, 2010
Bruce Croft, Donald Metzler and Trevor Strohman, Search Engines: Information
Retrieval in Practice, Addison Wesley, 2009.
Students are encouraged
to visit following links about
representative portals/ journals/ SIGs reporting research work in IR:
SOME OTHER interesting LINKS :
Singhal: Modern Information Retrieval- A Brief Overview - an old but useful
David Austin: How Google Finds Your Needle in the Web's Haystack
Croft: What Do People Want from Information Retrieval, Very old but still
IEEE Internet Computing Article, Sep-Oct. 1997
Links with pointers to more resources:
list of Information Retrieval resources by Chris Manning
Information Retrieval and the Web Research at Google
Slides and PDF copies of some reading material will be
shared as the class progresses.
More printed and online material, particularly related to the assignments, will
also be suggested.
Mid Semester Test (Open Book, Without Prior Notice)
- 20 Marks
Seminar (on a
topic of contemporary research in about 25 minutes) - 10 Marks
End Semester Examination - 70 Marks
Lab Exercises - 02 out of total 06 credits
LAB and PRESENTATION ASSIGNMENTS
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