Information retrieval

Information retrieval (IR) is the art and science of searching for information in documents, searching for documents themselves, searching for metadata which describe documents, or searching within databases, whether relational stand alone databases or hypertext networked databases such as the Internet or intranets, for text, sound, images or data. There is a common confusion, however, between data retrieval, document retrieval, information retrieval, and text retrieval, and each of these have their own bodies of literature, theory, praxis and technologies.

Model types

For a successful IR, it is necessary to represent the documents in some way. There are a number of models for this purpose roughly dividable into three main groups:

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Set-theoretic / Boolean models

• Standard Boolean model
• Extended Boolean model
• fuzzy retrieval

Algebraic / vector space models

• Vector space model
• Generalized vector space model
• Topic-based vector space model
• Enhanced topic-based vector space model
• Latent semantic indexing aka latent semantic analysis

Probabilistic models

• Binary independence retrieval
• Uncertain inference
• Language models
• Divergence from randomness models