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Information retrieval (IR) is the science of searching for documents, for information within documents and for metadata about documents, as well as that of searching relational databases and the World Wide Web. There is overlap in the usage of the terms data retrieval, document retrieval, information retrieval, and text retrieval, but each also has its own body of literature, theory, praxis and technologies. IR is interdisciplinary, based on computer science, mathematics, library science, information science, information architecture, cognitive psychology, linguistics, statistics and physics.

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Wikipedia about information retrieval

Information retrieval (IR) is the science of searching for documents, for information within documents and for metadata about documents, as well as that of searching relational databases and the World Wide Web. There is overlap in the usage of the terms data retrieval, document retrieval, information retrieval, and text retrieval, but each also has its own body of literature, theory, praxis and technologies. IR is interdisciplinary, based on computer science, mathematics, library science, information science, information architecture, cognitive psychology, linguistics, statistics and physics.

Automated information retrieval systems are used to reduce what has been called "information overload". Many universities and public libraries use IR systems to provide access to books, journals and other documents. Web search engines are the most visible IR applications.

History

The idea of using computers to search for relevant pieces of information was popularized in an article As We May Think by Vannevar Bush in 1945. First implementations of information retrieval systems were introduced in the 1950s and 1960s. By 1990 several different techniques had been shown to perform well on small text corpora (several thousand documents).

In 1992 the US Department of Defense, along with the National Institute of Standards and Technology (NIST), cosponsored the Text Retrieval Conference (TREC) as part of the TIPSTER text program. The aim of this was to look into the information retrieval community by supplying the infrastructure that was needed for evaluation of text retrieval methodologies on a very large text collection. This catalyzed research on methods that scale to huge corpora. The introduction of web search engines has boosted the need for very large scale retrieval systems even further.

The use of digital methods for storing and retrieving information has led to the phenomenon of digital obsolescence, where a digital resource ceases to be readable because the physical media, the reader required to read the media, the hardware, or the software that runs on it, is no longer available. The information is initially easier to retrieve than if it were on paper, but is then effectively lost.

Timeline

  • 1890: Hollerith tabulating machines were used to analyze the US census. (Herman Hollerith).
  • 1945: Vannevar Bush's As We May Think appeared in Atlantic Monthly
  • Late 1940s: The US military confronted problems of indexing and retrieval of wartime scientific research documents captured from Germans.
  • 1947: Hans Peter Luhn (research engineer at IBM since 1941) began work on a mechanized, punch card based system for searching chemical compounds.
  • 1950: The term "information retrieval" may have been coined by Calvin Mooers.
  • 1950s: Growing concern in the US for a "science gap" with the USSR motivated, encouraged funding, and provided a backdrop for mechanized literature searching systems (Allen Kent et al) and the invention of citation indexing (Eugene Garfield).
  • 1955: Allen Kent joined Case Western Reserve University, and eventually becomes associate director of the Center for Documentation and Communications Research. That same year, Kent and colleagues publish a paper in American Documentation describing the precision and recall measures, as well as detailing a proposed "framework" for evaluating an IR system, which includes statistical sampling methods for determining the number of relevant documents not retrieved.
  • 1958: International Conference on Scientific Information Washington DC included consideration of IR systems as a solution to problems identified. See: Proceedings of the International Conference on Scientific Information, 1958 (National Academy of Sciences, Washington, DC, 1959)
  • 1959: Hans Peter Luhn published "Auto-encoding of documents for information retrieval."
  • 1960: Melvin Earl (Bill) Maron and J. L. Kuhns published "On relevance, probabilistic indexing, and information retrieval" in Journal of the ACM 7(3):216-244, July 1960.
  • Early 1960s: Gerard Salton began work on IR at Harvard, later moved to Cornell.
  • 1962: Cyril W. Cleverdon published early findings of the Cranfield studies, developing a model for IR system evaluation. See: Cyril W. Cleverdon, "Report on the Testing and Analysis of an Investigation into the Comparative Efficiency of Indexing Systems". Cranfield Coll. of Aeronautics, Cranfield, England, 1962.
  • 1962: Kent published Information Analysis and Retrieval
  • 1963: Weinberg report "Science, Government and Information" gave a full articulation of the idea of a "crisis of scientific information." The report was named after Dr. Alvin Weinberg.
  • 1963: Joseph Becker and Robert M. Hayes published text on information retrieval. Becker, Joseph; Hayes, Robert Mayo. Information storage and retrieval: tools, elements, theories. New York, Wiley (1963).
  • 1964: Karen Spärck Jones finished her thesis at Cambridge, Synonymy and Semantic Classification, and continued work on computational linguistics as it applies to IR
  • 1964: The National Bureau of Standards sponsored a symposium titled "Statistical Association Methods for Mechanized Documentation." Several highly significant papers, including G. Salton's first published reference (we believe) to the SMART system.
  • Mid-1960s: National Library of Medicine developed MEDLARS Medical Literature Analysis and Retrieval System, the first major machine-readable database and batch retrieval system
  • Mid-1960s: Project Intrex at MIT
  • 1965: J. C. R. Licklider published Libraries of the Future
  • 1966: Don Swanson was involved in studies at University of Chicago on Requirements for Future Catalogs
  • 1968: Gerard Salton published Automatic Information Organization and Retrieval.
  • 1968: J. W. Sammon's RADC Tech report "Some Mathematics of Information Storage and Retrieval..." outlined the vector model.
  • 1969: Sammon's "A nonlinear mapping for data structure analysis" (IEEE Transactions on Computers) was the first proposal for visualization interface to an IR system.
  • Late 1960s: F. W. Lancaster completed evaluation studies of the MEDLARS system and published the first edition of his text on information retrieval
  • Early 1970s: first online systems--NLM's AIM-TWX, MEDLINE; Lockheed's Dialog; SDC's ORBIT
  • Early 1970s: Theodor Nelson promoting concept of hypertext, published Computer Lib/Dream Machines
  • 1971: N. Jardine and C. J. Van Rijsbergen published "The use of hierarchic clustering in information retrieval", which articulated the "cluster hypothesis." (Information Storage and Retrieval, 7(5), pp. 217-240, Dec 1971)
  • 1975: Three highly influential publications by Salton fully articulated his vector processing framework and term discrimination model:
  • A Theory of Indexing (Society for Industrial and Applied Mathematics)
  • "A theory of term importance in automatic text analysis", (JASIS v. 26)
  • "A vector space model for automatic indexing", (CACM 18:11)
  • 1978: The First ACM SIGIR conference.
  • 1979: C. J. Van Rijsbergen published Information Retrieval (Butterworths). Heavy emphasis on probabilistic models.
  • 1980: First international ACM SIGIR conference, joint with British Computer Society IR group in Cambridge
  • 1982: Belkin, Oddy, and Brooks proposed the ASK (Anomalous State of Knowledge) viewpoint for information retrieval. This was an important concept, though their automated analysis tool proved ultimately disappointing.
  • 1983: Salton (and M. McGill) published Introduction to Modern Information Retrieval (McGraw-Hill), with heavy emphasis on vector models.
  • Mid-1980s: Efforts to develop end user versions of commercial IR systems.
  • 1985-1993: Key papers on and experimental systems for visualization interfaces.
  • Work by D. B. Crouch, Robert R. Korfhage, M. Chalmers, A. Spoerri and others.
  • 1989: First World Wide Web proposals by Tim Berners-Lee at CERN.
  • 1992: First TREC conference.
  • 1997: Publication of Korfhage's Information Storage and Retrieval with emphasis on visualization and multi-reference point systems.
  • Late 1990s: Web search engine implementation of many features formerly found only in experimental IR systems

Search results for Information Retrieval

The Global Information Society Project

Global Information Society Project is focused on information, communication, and technology policy, and how it relates to global civil society, international ...www.information-retrieval.info/

AITopics / InformationRetrievalAndExtraction

The Center for Intelligent Information Retrieval at UMass. ... What Do People Want from Information Retrieval? ... From data storage to information retrieval. ...www.aaai.org/AITopics/html/info.html

Information Retrieval Resources

Classical and web information retrieval systems: algorithms, mathematical ... Books on Web Information Retrieval ... to Information Retrieval (see above) ...www-csli.stanford.edu/~hinrich/information-retrieval.html

Center for Intelligent Information Retrieval (CIIR)

... for Intelligent Information Retrieval (CIIR) is one of the leading research ... and visualization, digital libraries, and cross-lingual information retrieval. ...ciir.cs.umass.edu/

ACM SIGIR Special Interest Group on Information Retrieval Home Page

... acquisition, organization, storage, retrieval, and distribution of information. ... sustained and continuing contributions to research in information retrieval" ...www.sigir.org/

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News about Information Retrieval

GOOD MORNING -- September 16, 2008

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Face blindness research shows emotions are key in the study of face recognition

EurekAlert!Recognizing faces is usually an effortless process. However, a minority of people have difficulties identifying the person they are meeting or remembering people they have met before. These problems can be dramatic, where those affected fail to recognize the face of their spouse or child or even their own face. New research on face blindness demonstrates the importance of using naturalistic ...http://www.eurekalert.org/pub_releases/2008-09/plos-fbr09150...

Digital video ecosystem planned

TVNZA group of media industry companies said it is planning to build a digital world where video devices and content websites play together in perfect harmony, and consumers can safely store their digital content and access it anywhere in the world.http://tvnz.co.nz/view/page/411419/2073277

Wheels turn for children with sickle cell

Pittsburgh Post-GazetteEngines are revving and motorcyclists are strapping on their helmets, to ride their bikes for a good cause. ...http://www.post-gazette.com/pg/08261/912612-114.stm?cmpid=he...

MILF: AFP offering cash for bodies of soldiers

GMA NewsMANILA, Philippines - The Moro Islamic Liberation Front (MILF) accused the military Wednesday of endangering civilians' lives by offering up to P5,000 to recover the bodies of soldiers slain in battle.http://www.gmanews.tv/story/120866/MILF-AFP-offering-cash-fo...

News about Information Retrieval

Peter Cochrane's Blog: Social networking power

Silicon.comThis has led to new modes of working, information retrieval and distribution, followed by networked working and resourcing. My take is this is just the start of something very new! To date, social nets have been dominated by people in a fast-growing ... http://networks.silicon.com/webwatch/0,39024667,39291763,00....

Inmagic Taps SAVVIS for Social Knowledge Network Hosting in the Cloud

Businesswire.com ... is the company ’ s Web-based integrated library system (ILS) for Inmagic ® DB/Text — a specialized database optimized for text retrieval that lets users build networked and standalone textbases to manage information. Whether hosted ... http://www.businesswire.com/news/home/20081014006370/en

China Information Security Technology, Inc. Awarded $2.73 Million PGIS ...

MSN MoneyCentralThe installation will accelerate information collection and consolidation, display, enquiries and retrieval of vital statistics. With the application of CIST's unique PGIS correlation technology, raw business data can be processed into tables and ... http://news.moneycentral.msn.com/provider/providerarticle.as...

New Claims System Sets Avizent Apart

PR InsidePayment generation module - This module provides the tools to manage and generate payments for claims, and helps the user quickly access information through a built in "search and drill down" record retrieval inquiry. Additional VCS features are ... http://www.pr-inside.com/new-claims-system-sets-avizent-apar...

Basis Technology Powers Mark Logic Entity Enrichment

EarthtimesREX is designed for integration into software systems for information retrieval, text mining, relationship extraction, business intelligence, military intelligence, e-commerce and other applications that classify, analyze, and mine ... http://www.earthtimes.org/articles/show/basis-technology-pow...

Search results for Information Retrieval

Information Retrieval

Information Retrieval . Information retrieval research involves techniques from machine learning and other theoretical models, together with extensive experimentation to develop ... http://research.microsoft.com/ir/

Amazon.com: Information Retrieval: William Hersh: Books

Amazon.com: Information Retrieval: William Hersh: Books ... Information Retrieval and over 120,000 other books are available for Amazon Kindle – Amazon’s new wireless reading ... http://www.amazon.com/Information-Retrieval-William-Hersh/dp...

600.466 - Information Retrieval and Web Agents

600.466 Information Retrieval and Web Agents (Spring 2008) Instructor: David Yarowsky. TAs, Office Hours and Review Sections: Times and Locations; Final Exam Review:http://www.cs.jhu.edu/~yarowsky/cs466.html

Modern Information Retrieval

Information retrieval (IR) has changed considerably in the last years with the expansion of the Web (World Wide Web) and the advent of modern and inexpensive graphical user ... http://people.ischool.berkeley.edu/~hearst/irbook/

Information Retrieval for the 21st Century

Home | Contact Information | New Page Title Welcome to our web site! On this home page we'll introduce our business and highlight important ... http://INFORMATIONRETRIEVALFOR21ST.COM
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Answers for Information R...

Soroush

What is the differences between Push & Pull in Information Retrieval?

SoroushThe difference is in which machine is doing the bulk of the work. In a push, the source machine sends the information to the destination. In a pull, the destination goes to get it. Of course this is a...
olivier ertzscheid

Where can i get a definition and samples of serendipity in the field of information retrieval ?

olivier ertzscheidSerendipity is finding something unexpected and useful while searching for something else entirely. For instance, the discovery of the antibacterial properties of penicillin by Alexander Fleming is of...
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where can i find example of text mining system for information retrieval??

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jessica c

As a student what strategies & techniques you use in information retrieval on the internet?

jessica cNearly all research I do is to add to or modify a wiki article, thus information on Wikipedia, or any other wiki serves only as an assertion to be confirmed or shown to not be supported by a reliable ...
octaaas

why do people search (information retrieval systems)?

octaaasPlease tell me you're not in a LIS program.

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