Information Retrieval
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 |
|---|---|---|
| An Introduction to Information Retrieval | Christopher D. Manning, Prabhakar Raghavan & Hinrich Schütze | 1st (2009) |
| Recommender Systems Handbook | Francesco Ricci, Lior Rokach & Bracha Shapira | 2nd (2015) |
| Search Engines Information Retrieval in Practice | W. Bruce Croft, Donald Metzler & Trevor Strohman | 1st (2015) |
| Cross-Language Information Retrieval | Jian-Yun Nie Morgan & Claypool | 1st (2010) |
| Multimedia Information Retrieval | Stefan Rüger Morgan & Claypool | 1st (2010) |
| Information Retrieval: Implementing and Evaluating Search Engines | Stefan B¨uttcher, Charles L. A. Clarke & Gordon V. Cormack | 1st (2010) |
| Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data | Bing Liu | 2nd (2011) |
Videos
- 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