information retrieval information retrieval ir is the activity of obtaining information system resources relevant to an information need from a collection of information resources searches can be based on fulltext or other contentbased indexing information retrieval is the science of searching for information in a document searching for documents themselves and also searching for metadata that describe data and for databases of texts images or sounds automated information retrieval systems are used to reduce what has been called information overload an ir system is a software that provide access to books journals and other documents stores them and manages the document web search engines are the most visible ir applications overview an information retrieval process begins when a user enters a query into the system queries are formal statements of information needs for example search strings in web search engines in information retrieval a query does not uniquely identify a single object in the collection instead several objects may match the query perhaps with different degrees of relevancy an object is an entity that is represented by information in a content collection or database user queries are matched against the database information however as opposed to classical sql queries of a database in information retrieval the results returned may or may not match the query so results are typically ranked this ranking of results is a key difference of information retrieval searching compared to database searching depending on the application the data objects may be for example text documents images or videos often the documents themselves are not kept or stored directly in the ir system but are instead represented in the system by document surrogates or metadata most ir systems compute a numeric score on how well each object in the database matches the query and rank the objects according to this value the top ranking objects are then shown to the user the process may then be iterated if the user wishes to refine the query history there is a machine called the univac whereby letters and figures are coded as a pattern of magnetic spots on a long steel tape by this means the text of a document preceded by its subject code symbol ca be recorded the machine automatically selects and types out those references which have been coded in any desired way at a rate of 120 words a minute j e holmstrom 1948 the idea of using computers to search for relevant pieces of information was popularized in the article as we may think by vannevar bush in 1945 largescale retrieval systems such as the lockheed dialog system came into use early in the 1970s 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 model types categorization of irmodels translated from german entry original source dominik kuropka for effectively retrieving relevant documents by ir strategies the documents are typically transformed into a suitable representation each retrieval strategy incorporates a specific model for its document representation purposes the picture on the right illustrates the relationship of some common models in the picture the models are categorized according to two dimensions the mathematical basis and the properties of the model first dimension mathematical basis settheoretic models represent documents as sets of words or phrases similarities are usually derived from settheoretic operations on those sets common models are standard boolean model extended boolean model fuzzy retrieval algebraic models represent documents and queries usually as vectors matrices or tuples the similarity of the query vector and document vector is represented as a scalar value vector space model generalized vector space model enhanced topicbased vector space model extended boolean model latent semantic indexing aka latent semantic analysis probabilistic models treat the process of document retrieval as a probabilistic inference similarities are computed as probabilities that a document is relevant for a given query probabilistic theorems like the bayes theorem are often used in these models binary independence model probabilistic relevance model on which is based the okapi bm25 relevance function uncertain inference language models divergencefromrandomness model latent dirichlet allocation featurebased retrieval models view documents as vectors of values of feature functions or just features and seek the best way to combine these features into a single relevance score typically by learning to rank methods feature functions are arbitrary functions of document and query and as such can easily incorporate almost any other retrieval model as just another feature second dimension properties of the model models without terminterdependencies treat different termswords as independent this fact is usually represented in vector space models by the orthogonality assumption of term vectors or in probabilistic models by an independency assumption for term variables models with immanent term interdependencies allow a representation of interdependencies between terms however the degree of the interdependency between two terms is defined by the model itself it is usually directly or indirectly derived eg by dimensional reduction from the cooccurrence of those terms in the whole set of documents models with transcendent term interdependencies allow a representation of interdependencies between terms but they do not allege how the interdependency between two terms is defined they rely an external source for the degree of interdependency between two terms for example a human or sophisticated algorithms performance and correctness measures evaluation measures information retrieval the evaluation of an information retrieval system is the process of assessing how well a system meets the information needs of its users in general measurement considers a collection of documents to be searched and a search query traditional evaluation metrics designed for boolean retrieval or topk retrieval include precision and recall all measures assume a ground truth notion of relevancy every document is known to be either relevant or nonrelevant to a particular query in practice queries may be illposed and there may be different shades of relevancy timeline before the 1900s 1801 joseph marie jacquard invents the jacquard loom the first machine to use punched cards to control a sequence of operations 1880s herman hollerith invents an electromechanical data tabulator using punch cards as a machine readable medium 1890 hollerith cards keypunches and tabulators used to process the 1890 us census data 1920s1930s emanuel goldberg submits patents for his statistical machine a document search engine that used photoelectric cells and pattern recognition to search the metadata on rolls of microfilmed documents 1940s1950s late 1940s the us military confronted problems of indexing and retrieval of wartime scientific research documents captured from germans 1945 vannevar bushs as we may think appeared in atlantic monthly 1947 hans peter luhn research engineer at ibm since 1941 began work on a mechanized punch cardbased system for searching chemical compounds 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 1950 the term information retrieval was coined by calvin mooers 1951 philip bagley conducted the earliest experiment in computerized document retrieval in a master thesis at mit 1955 allen kent joined case western reserve university and eventually became associate director of the center for documentation and communications research that same year kent and colleagues published a paper in american documentation describing the precision and recall measures as well as detailing a proposed framework for evaluating an ir system which included 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 autoencoding of documents for information retrieval 1960s early 1960s gerard salton began work on ir at harvard later moved to cornell 1960 melvin earl maron and john lary kuhns published on relevance probabilistic indexing and information retrieval in the journal of the acm 73216244 july 1960 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 collection of aeronautics cranfield england 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 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 sprck jones finished her thesis at cambridge synonymy and semantic classification and continued work on computational linguistics as it applies to ir the national bureau of standards sponsored a symposium titled statistical association methods for mechanized documentation several highly significant papers including g saltons first published reference we believe to the smart system mid1960s national library of medicine developed medlars medical literature analysis and retrieval system the first major machinereadable database and batchretrieval system 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 late 1960s f wilfrid lancaster completed evaluation studies of the medlars system and published the first edition of his text on information retrieval 1968 gerard salton published automatic information organization and retrieval john w sammon jrs radc tech report some mathematics of information storage and retrieval outlined the vector model 1969 sammons a nonlinear mapping for data structure analysis ieee transactions on computers was the first proposal for visualization interface to an ir system 1970s early 1970s first online systemsnlms aimtwx medline lockheeds dialog sdcs orbit theodor nelson promoting concept of hypertext published computer libdream machines 1971 nicholas jardine and cornelis j van rijsbergen published the use of hierarchic clustering in information retrieval which articulated the cluster hypothesis 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 1811 1978 the first acm sigir conference 1979 c j van rijsbergen published information retrieval butterworths heavy emphasis on probabilistic models 1979 tamas doszkocs implemented the cite natural language user interface for medline at the national library of medicine the cite system supported free form query input ranked output and relevance feedback 1980s 1980 first international acm sigir conference joint with british computer society ir group in cambridge 1982 nicholas j belkin robert n oddy and helen m 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 michael j mcgill published introduction to modern information retrieval mcgrawhill with heavy emphasis on vector models 1985 david blair and bill maron publish an evaluation of retrieval effectiveness for a fulltext documentretrieval system mid1980s efforts to develop enduser versions of commercial ir systems 19851993 key papers on and experimental systems for visualization interfaces work by donald b crouch robert r korfhage matthew chalmers anselm spoerri and others 1989 first world wide web proposals by tim bernerslee at cern 1990s 1992 first trec conference 1997 publication of korfhages information storage and retrieval with emphasis on visualization and multireference point systems 1999 publication of ricardo baezayates and berthier ribeironetos modern information retrieval by addison wesley the first book that attempts to cover all ir late 1990s web search engines implementation of many features formerly found only in experimental ir systems search engines become the most common and maybe best instantiation of ir models major conferences sigir conference on research and development in information retrieval ecir european conference on information retrieval cikm conference on information and knowledge management www international world wide web conference wsdm conference on web search and data mining ictir international conference on theory of information retrieval awards in the field tony kent strix award gerard salton award top 5 leading ir research groups center for intelligent information retrieval ciir at the university of massachusetts amherst information retrieval group at the university of glasgow information and language processing systems ilps at the university of amsterdam information retrieval group thuir at tsinghua university information storage analysis and retrieval group isar at rmit university adversarial information retrieval collaborative information seeking computer memory controlled vocabulary crosslanguage information retrieval data mining european summer school in information retrieval humancomputer information retrieval hcir information extraction information retrieval facility knowledge visualization multimedia information retrieval personal information management relevance information retrieval relevance feedback rocchio classification search index social information seeking special interest group on information retrieval subject indexing temporal information retrieval tfidf xml retrieval web mining ricardo baezayates berthier ribeironeto modern information retrieval the concepts and technology behind search second edition addisonwesley uk 2011 stefan bttcher charles l a clarke and gordon v cormack information retrieval implementing and evaluating search engines mit press cambridge massachusetts 2010 christopher d manning prabhakar raghavan and hinrich schtze introduction to information retrieval cambridge university press 2008 wikiquote has quotations related to information retrieval wikimedia commons has media related to information retrieval acm sigir information retrieval special interest group bcs irsg british computer society information retrieval specialist group text retrieval conference trec forum for information retrieval evaluation fire information retrieval online book by c j van rijsbergen information retrieval wiki information retrieval facility information retrieval duth trec report on information retrieval evaluation techniques how ebay measures search relevance information retrieval performance evaluation tool athena research centre authority control gnd 40728031 lccn sh85066148 ndl 00575010 