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  2. Learning to rank - Wikipedia

    en.wikipedia.org/wiki/Learning_to_rank

    In this case, the learning-to-rank problem is approximated by a classification problem — learning a binary classifier (,) that can tell which document is better in a given pair of documents. The classifier shall take two documents as its input and the goal is to minimize a loss function L ( h ; x u , x v , y u , v ) {\displaystyle L(h;x_{u},x ...

  3. Ranking SVM - Wikipedia

    en.wikipedia.org/wiki/Ranking_SVM

    In machine learning, a ranking SVM is a variant of the support vector machine algorithm, which is used to solve certain ranking problems (via learning to rank). The ranking SVM algorithm was published by Thorsten Joachims in 2002. [1] The original purpose of the algorithm was to improve the performance of an internet search engine.

  4. File:RelativeRankLearning2.pdf - Wikipedia

    en.wikipedia.org/wiki/File:RelativeRankLearning2.pdf

    English: Learning in the partial-information sequential search paradigm. The numbers display the expected values of applicants based on their relative rank (out of m total applicants seen so far) at various points in the search. Expectations are calculated based on the case when their values are uniformly distributed between 0 and 1.

  5. Ranking (information retrieval) - Wikipedia

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

    Ranking of query is one of the fundamental problems in information retrieval (IR), [1] the scientific/engineering discipline behind search engines. [2] Given a query q and a collection D of documents that match the query, the problem is to rank, that is, sort, the documents in D according to some criterion so that the "best" results appear early in the result list displayed to the user.

  6. Okapi BM25 - Wikipedia

    en.wikipedia.org/wiki/Okapi_BM25

    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.

  7. Open Library - Wikipedia

    en.wikipedia.org/wiki/Open_Library

    Open Library is an online project intended to create "one web page for every book ever published". Created by Aaron Swartz, [3] [4] Brewster Kahle, [5] Alexis Rossi, [6] Anand Chitipothu, [6] and Rebecca Hargrave Malamud, [6] Open Library is a project of the Internet Archive, a nonprofit organization.

  8. Active learning (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Active_learning_(machine...

    Active learning is a special case of machine learning in which a learning algorithm can interactively query a human user (or some other information source), to label new data points with the desired outputs. The human user must possess knowledge/expertise in the problem domain, including the ability to consult/research authoritative sources ...

  9. GPT-1 - Wikipedia

    en.wikipedia.org/wiki/GPT-1

    Download as PDF; Printable version; ... Feature learning; Learning to rank; Grammar induction; ... It contained over 7,000 unpublished fiction books from various ...