enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  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. 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. [51] [52]

  5. Timeline of web search engines - Wikipedia

    en.wikipedia.org/wiki/Timeline_of_web_search_engines

    Robin Li developed the RankDex site-scoring algorithm for search engines results page ranking [23] [24] [25] and received a US patent for the technology. [26] It was the first search engine that used hyperlinks to measure the quality of websites it was indexing, [ 27 ] predating the very similar algorithm patent filed by Google two years later ...

  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. It is based on the probabilistic retrieval framework developed in the 1970s and 1980s by Stephen E. Robertson , Karen Spärck Jones , and others.

  7. Search engine - Wikipedia

    en.wikipedia.org/wiki/Search_engine

    They can either submit one web page at a time, or they can submit the entire site using a sitemap, but it is normally only necessary to submit the home page of a web site as search engines are able to crawl a well designed website. There are two remaining reasons to submit a web site or web page to a search engine: to add an entirely new web ...

  8. Category:Internet search algorithms - Wikipedia

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

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

  9. Discounted cumulative gain - Wikipedia

    en.wikipedia.org/wiki/Discounted_cumulative_gain

    Discounted cumulative gain (DCG) is a measure of ranking quality in information retrieval. It is often normalized so that it is comparable across queries, giving Normalized DCG (nDCG or NDCG). NDCG is often used to measure effectiveness of search engine algorithms and related applications.