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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.
Cumulative Gain is the sum of the graded relevance values of all results in a search result list. CG does not take into account the rank (position) of a result in the result list. The CG at a particular rank position is defined as: = = Where is the graded relevance of the result at position . The value computed with the CG function is ...
A search engine called "RankDex" from IDD Information Services, designed by Robin Li in 1996, developed a strategy for site-scoring and page-ranking. [15] 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 ...
Alternatively, training data may be derived automatically by analyzing clickthrough logs (i.e. search results which got clicks from users), [3] query chains, [4] or such search engines' features as Google's (since-replaced) SearchWiki. Clickthrough logs can be biased by the tendency of users to click on the top search results on the assumption ...
Evaluation of IR systems is central to the success of any search engine including internet search, website search, databases and library catalogues. Evaluations measures are used in studies of information behaviour, usability testing, business costs and efficiency assessments.
Domain Authority (DA), a website metric developed by Moz, is a predictive metric to determine a website's traffic and organic search engine rankings. Domain Authority is based on different link metrics, such as number of linking root domains, number of total backlinks, and the distance of backlinks from the home page of websites.
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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.