awesome-information-retrieval

C.D. Manning, P. Raghavan, H. Schütze. Cambridge UP, 2008. (First book for getting started with Information Retrieval)

Bruce Croft, Don Metzler, and Trevor Strohman. 2009. (Great book for readers interested in knowing how Search Engines work. The book is very detailed)

R. Baeza-Yates, B. Ribeiro-Neto. Addison-Wesley, 1999

B. Croft, D. Metzler, T. Strohman. Pearson Education, 2009

S. Chakrabarti. Morgan Kaufmann, 2002

W.B. Croft, J. Lafferty. Springer, 2003. (Handles Language Modeling aspect of Information Retrieval. It also extensively details probabilistic perspective in this domain, which is interesting)

Ed Greengrass, 2000. (Comprehensive survey of Conventional Information Retrieval, before Deep Learning era)

G.G. Chowdhury. Neal-Schuman, 2003. (Intended for students of library and information studies)

C.T. Meadow, B.R. Boyce, D.H. Kraft, C.L. Barry. Academic Press, 2007 (library/information science perspective)

Matthew Lease (University of Texas at Austin)

Chris Manning and Pandu Nayak (Stanford University)

Raymond J. Mooney (University of Texas at Austin)

Vagelis Hristidis (University of California - Riverside)

Ray R. Larson (UC berkeley)

Jamie Callan (CMU)

David Yarowsky (John Hopkins University)

Andrea LaPaugh (Princeton University)

Dr. Jilles Vreeken , Prof. Dr. Gerhard Weikum (MPI)

Prof. ChengXiang Zhai (University of Illinois at Urbana-Champaign)

Open Source Search Engine that can be used to test Information Retrieval Algorithm. Twitter uses this core for its real-time search

The Lemur Project develops search engines, browser toolbars, text analysis tools, and data resources that support research and development of information retrieval and text mining software

Another Open Source Search Engine competitor of Apache Lucene

Open Source Toolkit for research in Language Modeling, filtering and categorization

Linked data web

This is one of the first collections in IR domain, however the dataset is too small for any statistical significance analysis, but is nevertheless suitable for pilot runs

TREC is the benchmark dataset used by most IR and Web search algorithms. It has several tracks, each of which consists of dataset to test for a specific task. The tracks along with suggested use-case are:

Explore information seeking behavior in the blogosphere

Address challenges in building large chemical testbeds for chemical IR

Investigate techniques to link medical cases to information relevant for patient care

Study problem

Investigate search techniques for complex information needs (context and user interests based)

Explore crowdsourcing methods for performing and evaluating search

Study search over the organization data

Perform entity-related search (find entities and their properties) on Web data

Binarily decide retrieval of new incoming documents given a stable information need

Study merge performance for results from various search services

Study retrieval efficiency of genomics data and corresponding documentation

Obtain High Accuracy Retrieval from Documents by leveraging searcher's context

Study user interaction with text retrieval systems

Study algorithms that improve efficiency of human Knowledge Base

Study retrieval systems that have high recall for legal documents use case

Explore unstructured search performance over patients record data

Examine satisfaction of real-time information need for microblogging sites

Explore ad-hoc retrieval over large set of queries

Investigate systems' abilities to locate new (non-redundant) information

Test systems that scale beyond document retrieval, to retrieve answers to factoid, list and definition type questions

For deep evaluation of relevance feedback processes

Study individual topic's effectiveness

Develop methods for measuring multiple-query sessions where information needs drift

Benchmark spam filtering approaches

Test if systems can induce possible tasks, users might be trying to accomplish for the query

Develop systems that allow users to efficiently monitor the information associated with an event over time

Test scalability of IR systems to large scale collection

Explore information seeking behaviors common in general web search

This is one of the largest Web collection of documents obtained from crawl of government websites by Charlie Clarke and Ian Soboroff, using NIST hardware and network, then formatted by Nick Craswel

This is collection of wide variety of dataset ranging from Ad-hoc collection, Chinese IR collection, mobile clickthrough collections to medical collections. The focus of this collection is mostly on east asian languages and cross language information retrieval

This dataset can be used for cross lingual IR between CJKE (Chinese-Japanese-Korean-English) languages. It is suitable for the following tasks:

It supports following bi-lingua and mono-lingua:

The dataset is used for the task of cross-lingual question answering but the complexity of the task is higher than CLQA dataset

It contains a multi-lingual document collection. The test suite includes:

The corpora is now available through NIST. The corpora includes following:

This data set consists of 20000 newsgroup messages.posts taken from 20 newsgroup topics

This data set is a comprehensive archive of English newswire text data including headlines, datelines and articles

Past newswire/paper datasets (DUC 2001 - DUC 2007) are available upon request

Manik Verma (Microsoft Research)

Tim Berners-Lee (Ted Talk) [Tim Berners-Lee invented the World Wide Web. He leads the World Wide Web Consortium (W3C), overseeing the Web's standards and development]

Gary Flake, Technical Fellow at Microsoft (TED Talks)

Jeff Dean (WSDM Conference, 2009)

David Wilne (The University of Waikato, 2008)

Steve Tjoa (RackSpace Developers) [This talk shows that IR is not just text and images]

Liron Shapira (Box Tech Talk)

Doug Imbruce (Techcrunch Disrupt)[Doug Imbruce is the Founder of Qwiki, Inc, a technology startup in New York, NY, acquired by Yahoo! in 2013]

Dr. Alma Whitten (Google Brussels Tech Talk)

Andreas Ekström (Swedish Author & Journalist, TED Talk)

Eli Pariser (Author of the Filter Bubble, TED Talk)

Andy Yen (CERN, TED Talk) [This talk talks about privacy, which Search Engines intrude into, and how can people protect it]

Michael Douglas [TEDx SouthBank]

Christopher "moot" Poole" (Ted Talks) [Christopher "moot" Poole is founder of 4chan, an online imageboard whose anonymous denizens have spawned the web's most bewildering and influential subculture]

Web Search and Data Mining Conference -

Special Interests Group on Information Retrieval -

Text REtrieval Conference -

European Conference on Information Retrieval -

World Wide Web Conference -

Conference on Information and Knowledge Management -

Forum for Information Retrieval Evaluation -

Conference and Labs of the Evaluation Forum -

NII Testsbeds and Community for Information access Research -

Google Research

Dr. Edel Garcia

Information Extraction

Information Retrieval from Lip Reading

Bias in Relevance

Sketch-based search

Information Extraction