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  2. Learning to rank - Wikipedia

    en.wikipedia.org/wiki/Learning_to_rank

    They may be used to compute document's static quality score (or static rank), which is often used to speed up search query evaluation. [7] [10] Query-dependent or dynamic features — those features, which depend both on the contents of the document and the query, such as TF-IDF score or other non-machine-learned ranking functions.

  3. 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.

  4. PageRank - Wikipedia

    en.wikipedia.org/wiki/PageRank

    PageRank (PR) is an algorithm used by Google Search to rank web pages in their search engine results. It is named after both the term "web page" and co-founder Larry Page . PageRank is a way of measuring the importance of website pages.

  5. Glicko rating system - Wikipedia

    en.wikipedia.org/wiki/Glicko_rating_system

    Mark Glickman created the Glicko rating system in 1995 as an improvement on the Elo rating system. [1]Both the Glicko and Glicko-2 rating systems are under public domain and have been implemented on game servers online like Counter-Strike: Global Offensive, Team Fortress 2, [2] Dota 2, [3] Guild Wars 2, [4] Splatoon 2, [5] Online-go.com, [6] Lichess and Chess.com.

  6. Ranking SVM - Wikipedia

    en.wikipedia.org/wiki/Ranking_SVM

    The ranking SVM algorithm is a learning retrieval function that employs pairwise ranking methods to adaptively sort results based on how 'relevant' they are for a specific query. The ranking SVM function uses a mapping function to describe the match between a search query and the features of each of the possible results.

  7. Potentially all pairwise rankings of all possible alternatives

    en.wikipedia.org/wiki/Potentially_all_pairwise...

    Because the three pairwise rankings above are consistent – and all n (n−1)/2 = 28 pairwise rankings (n = 8) for this simple value model are known – a complete overall ranking of all eight possible alternatives is defined (1st to 8th): 222, 122, 221, 212, 121, 112, 211, 111.

  8. Ranking (statistics) - Wikipedia

    en.wikipedia.org/wiki/Ranking_(statistics)

    In statistics, ranking is the data transformation in which numerical or ordinal values are replaced by their rank when the data are sorted. For example, if the numerical data 3.4, 5.1, 2.6, 7.3 are observed, the ranks of these data items would be 2, 3, 1 and 4 respectively.

  9. Kendall tau distance - Wikipedia

    en.wikipedia.org/wiki/Kendall_tau_distance

    The Kendall tau distance between two rankings is the number of pairs that are in different order in the two rankings. For example, the Kendall tau distance between 0 3 1 6 2 5 4 and 1 0 3 6 4 2 5 is four because the pairs 0-1, 3-1, 2-4, 5-4 are in different order in the two rankings, but all other pairs are in the same order. [1]