SMART Information Retrieval System

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A SMART Information Retrieval System is a Information Retrieval System that includes Vector Space Modelling, Relevance Feedback, and Rocchio Classification.



References

2019

  • (Wikipedia, 2019) ⇒ https://en.wikipedia.org/wiki/SMART_Information_Retrieval_System Retrieved:2019-12-21.
    • The SMART (System for the Mechanical Analysis and Retrieval of Text) Information Retrieval System is an information retrieval system developed at Cornell University in the 1960s. Many important concepts in information retrieval were developed as part of research on the SMARTsystem, including the vector space model, relevance feedback, and Rocchio classification.

      Gerard Salton led the group that developed SMART. Other contributors included Mike Lesk.

      The SMART system also provides a set of corpora, queries and reference rankings, taken from different subjects, notably

    • To the legacy of the SMART system belongs the so-called SMART triple notation, a mnemonic scheme for denoting tf-idf weighting variants in the vector space model. The mnemonic for representing a combination of weights takes the form ddd.qqq, where the first three letters represents the term weighting of the collection document vector and the second three letters represents the term weighting for the query document vector. For example, ltc.lnn represents the ltc weighting applied to a collection document and the lnn weighting applied to a query document.

      The following tables establish the SMART notation: The gray letters in the first, fifth, and ninth columns are the scheme used by Salton and Buckley in their 1988 paper. [1] The bold letters in the second, sixth, and tenth columns are the scheme used in experiments reported thereafter.

  1. Salton, G., & Buckley, C. (1988). Term-Weighting Approaches in Automatic Text Retrieval. Inf. Process. Manage., 24, 513-523.

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