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  2. 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.

  3. PageRank - Wikipedia

    en.wikipedia.org/wiki/PageRank

    Li referred to his search mechanism as "link analysis," which involved ranking the popularity of a web site based on how many other sites had linked to it. [16] RankDex, the first search engine with page-ranking and site-scoring algorithms, was launched in 1996. [17] Li filed a patent for the technology in RankDex in 1997; it was granted in ...

  4. Discounted cumulative gain - Wikipedia

    en.wikipedia.org/wiki/Discounted_cumulative_gain

    The nDCG values for all queries can be averaged to obtain a measure of the average performance of a search engine's ranking algorithm. Note that in a perfect ranking algorithm, the will be the same as the producing an nDCG of 1.0. All nDCG calculations are then relative values on the interval 0.0 to 1.0 and so are cross-query comparable.

  5. Okapi BM25 - Wikipedia

    en.wikipedia.org/wiki/Okapi_BM25

    The fuller name, Okapi BM25, includes the name of the first system to use it, which was the Okapi information retrieval system, implemented at London's City University [1] in the 1980s and 1990s. BM25 and its newer variants, e.g. BM25F (a version of BM25 that can take document structure and anchor text into account), represent TF-IDF -like ...

  6. Category:Internet search algorithms - Wikipedia

    en.wikipedia.org/wiki/Category:Internet_search...

    Algorithms used in web search engines. See Category:Ranking functions for ranking algorithms suitable for document retrieval in non-web systems. Subcategories.

  7. Learning to rank - Wikipedia

    en.wikipedia.org/wiki/Learning_to_rank

    Commercial web search engines began using machine-learned ranking systems since the 2000s (decade). One of the first search engines to start using it was AltaVista (later its technology was acquired by Overture , and then Yahoo ), which launched a gradient boosting -trained ranking function in April 2003.

  8. AOL

    search.aol.com

    The search engine that helps you find exactly what you're looking for. Find the most relevant information, video, images, and answers from all across the Web.

  9. TrustRank - Wikipedia

    en.wikipedia.org/wiki/TrustRank

    Today, this algorithm is a part of major web search engines like Yahoo! and Google. [2] One of the most important factors that help web search engine determine the quality of a web page when returning results are backlinks. Search engines take a number and quality of backlinks into consideration when assigning a place to a certain web page in ...