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Information Retrieval

PreviouscoursesNextData Mining

Last updated 5 years ago

Overview

Information retrieval (IR) deals with retrieving information efficiently from documents, web, multimedia and a lot more. This course covers the following topics:

  • Queries: Boolean, Phrase, Wildcard, Permuterm, Shingling, Jaccard, Cosine, tf-idf

  • Algorithms: Hashes, B-Trees, Edit distance, Soundex, LZW Compression, Porter Stemming

  • Indexing: Inverted, Positional, BSBI, SPMI, Distributed, Dynamic

  • Multimedia: Image, Audio, Video, Watermarking, Fingerprinting

  • Web: Searching, Crawling, Page Rank, SEO, Spam

  • Recommender Systems: Collaborative, Content-Based, Hybrid

  • Cross Language: Query Translation, Document Translation, Corpus & Knowledge based techniques

Navigation

Prerequisites

This course has no prerequisites.

Textbooks

Title

Author(s)

Edition

Christopher D. Manning, Prabhakar Raghavan & Hinrich Schütze

1st (2009)

Francesco Ricci, Lior Rokach & Bracha Shapira

2nd (2015)

W. Bruce Croft, Donald Metzler & Trevor Strohman

1st (2015)

Jian-Yun Nie Morgan & Claypool

1st (2010)

Stefan Rüger Morgan & Claypool

1st (2010)

Stefan B¨uttcher, Charles L. A. Clarke & Gordon V. Cormack

1st (2010)

Bing Liu

2nd (2011)

Videos

Websites

IR Course, Simeon
IR Course, itechnica
Edit Distance, Gaurav Sen
How Shazam Works, Real Engineering
tf-idf, RevMachineLearning
Stemming, Stanford
Recommender Systems, CS50
Content Based Recommendations, Stanford
Collaborative Filtering, Stanford
Image Detection: Watermarking vs. Fingerprinting, Jonathan Bailey
What is image hashing used for?, Stack Overflow
What is audio fingerprinting?, Dan Gravell
Understanding basics of Recommendation Engines, Analytics Vidhya
Prerequisites
Textbooks
Videos
Websites
An Introduction to Information Retrieval
Recommender Systems Handbook
Search Engines Information Retrieval in Practice
Cross-Language Information Retrieval
Multimedia Information Retrieval
Information Retrieval: Implementing and Evaluating Search Engines
Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data