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  2. Relevance feedback - Wikipedia

    en.wikipedia.org/wiki/Relevance_feedback

    Relevance feedback is a feature of some information retrieval systems. The idea behind relevance feedback is to take the results that are initially returned from a given query, to gather user feedback, and to use information about whether or not those results are relevant to perform a new query. We can usefully distinguish between three types ...

  3. Relevance (information retrieval) - Wikipedia

    en.wikipedia.org/wiki/Relevance_(information...

    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. [2]

  4. Evaluation measures (information retrieval) - Wikipedia

    en.wikipedia.org/wiki/Evaluation_measures...

    Evaluation measures for an information retrieval (IR) system assess how well an index, search engine, or database returns results from a collection of resources that satisfy a user's query. They are therefore fundamental to the success of information systems and digital platforms.

  5. File:Section Translation Feedback Survey (Final report).pdf

    en.wikipedia.org/wiki/File:Section_Translation...

    You are free: to share – to copy, distribute and transmit the work; to remix – to adapt the work; Under the following conditions: attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made.

  6. Information retrieval - Wikipedia

    en.wikipedia.org/wiki/Information_retrieval

    Traditional evaluation metrics, designed for Boolean retrieval [clarification needed] or top-k retrieval, include precision and recall. All measures assume a ground truth notion of relevance: every document is known to be either relevant or non

  7. Rocchio algorithm - Wikipedia

    en.wikipedia.org/wiki/Rocchio_algorithm

    The Rocchio algorithm is based on a method of relevance feedback found in information retrieval systems which stemmed from the SMART Information Retrieval System developed between 1960 and 1964. Like many other retrieval systems, the Rocchio algorithm was developed using the vector space model .

  8. XML retrieval - Wikipedia

    en.wikipedia.org/wiki/XML_Retrieval

    Ranking in XML-Retrieval can incorporate both content relevance and structural similarity, which is the resemblance between the structure given in the query and the structure of the document. Also, the retrieval units resulting from an XML query may not always be entire documents, but can be any deeply nested XML elements, i.e. dynamic documents.

  9. Member check - Wikipedia

    en.wikipedia.org/wiki/Member_check

    In qualitative research, a member check, also known as informant feedback or respondent validation, is a technique used by researchers to help improve the accuracy, credibility, validity, and transferability (also known as applicability, internal validity, [1] or fittingness) of a study. [2]