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Information retrieval is the science [1] of searching for information in a document, searching for documents themselves, and also searching for the metadata that describes 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 ...
Databases and search engines differ substantially in terms of coverage and retrieval qualities. [1] Users need to account for qualities and limitations of databases and search engines, especially those searching systematically for records such as in systematic reviews or meta-analyses. [ 2 ]
The information retrieval community has emphasized the use of test collections and benchmark tasks to measure topical relevance, starting with the Cranfield Experiments of the early 1960s and culminating in the TREC evaluations that continue to this day as the main evaluation framework for information retrieval research.
Indexing and classification methods to assist with information retrieval have a long history dating back to the earliest libraries and collections however systematic evaluation of their effectiveness began in earnest in the 1950s with the rapid expansion in research production across military, government and education and the introduction of computerised catalogues.
The International Journal of Multimedia Information Retrieval is a quarterly peer-reviewed scientific journal published by Springer Science+Business Media covering all aspects of multimedia information retrieval. It was established in 2012 and the editor-in-chief is Michael Lew (University of Leiden).
Additionally, SIGIR presents a Best Paper Award [1] to recognize the highest quality paper at each conference. "Test of time" Award [ 2 ] is a recent award that is given to a paper that has had "long-lasting influence, including impact on a subarea of information retrieval research, across subareas of information retrieval research, and outside ...
In information retrieval, Okapi BM25 (BM is an abbreviation of best matching) is a ranking function used by search engines to estimate the relevance of documents to a given search query. It is based on the probabilistic retrieval framework developed in the 1970s and 1980s by Stephen E. Robertson, Karen Spärck Jones, and others.
Question answering (QA) is a computer science discipline within the fields of information retrieval and natural language processing (NLP) that is concerned with building systems that automatically answer questions that are posed by humans in a natural language. [1]