Information retrieval

Overview and History of Information Retrieval
– Information retrieval process begins with a user query
– Queries are formal statements of information needs
– Multiple objects may match a query with varying relevance
– Objects can be text documents, images, audio, mind maps, or videos
– IR systems rank results based on query-object match and relevance
– Vannevar Bush popularized the idea of using computers for information retrieval in 1945
– Emanuel Goldberg filed patents for a statistical machine for document search in the 1920s and 1930s
– Holmstrom described the first computer searching for information in 1948
– Automated information retrieval systems were introduced in the 1950s
– Large-scale retrieval systems like Lockheed Dialog came into use in the 1970s

Mathematical Models in Information Retrieval
– Set-theoretic models represent documents as sets of words or phrases
– Algebraic models represent documents and queries as vectors, matrices, or tuples
– Probabilistic models treat document retrieval as probabilistic inference
– Feature-based retrieval models view documents as vectors of feature values
– Each model has different mathematical foundations and properties

Term Interdependencies in Information Retrieval Models
– Models without term-interdependencies treat terms as independent
– Models with immanent term interdependencies allow representation of interdependencies between terms
– Models with transcendent term interdependencies rely on external sources for interdependency definition
– The degree of interdependency between terms is defined by the model itself or derived from co-occurrence
– Different models have different approaches to representing term interdependencies

Performance and Correctness Measures in Information Retrieval
– Evaluation measures assess how well an IR system meets user information needs
– Traditional metrics include precision and recall for Boolean or top-k retrieval
– Ground truth notion of relevance is assumed for evaluation
– Queries may be ill-posed and relevance shades may vary
– Evaluation measures help assess the performance and correctness of an IR system

Key Contributors, Development, and Awards in Information Retrieval
– Eugene Garfield: Invented the citation index
– Calvin Mooers: Coined the term ‘information retrieval’
– Philip Bagley: Conducted the earliest experiment in computerized document retrieval
– Allen Kent: Published a paper describing precision and recall measures and proposed an evaluation framework for IR systems
– Hans Peter Luhn: Published a paper on auto-encoding of documents for information retrieval
– Gerard Salton: Began work on IR at Harvard and later moved to Cornell, outlined the vector model
– Karen Spärck Jones: Continued work on computational linguistics as it applies to IR
– Major conferences in information retrieval include SIGIR, ECIR, CIKM, WWW, and WSDM
– Awards in the field of information retrieval include the Tony Kent Strix award, Gerard Salton Award, and Karen Spärck Jones Award