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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 possible architecture of a machine-learned search engine. Ranking is a central part of many information retrieval problems, such as document retrieval, collaborative filtering, sentiment analysis, and online advertising. A possible architecture of a machine-learned search engine is shown in the accompanying figure.
Indexing and classification methods to assist with information retrieval have a long history dating back to the earliest libraries and collections however systematic evaluation of their effectiveness began in earnest in the 1950s with the rapid expansion in research production across military, government and education and the introduction of computerised catalogues.
Cross-platform open-source desktop search engine. Unmaintained since 2011-06-02 [9]. LGPL v2 [10] Terrier Search Engine: Linux, Mac OS X, Unix: Desktop search for Windows, Mac OS X (Tiger), Unix/Linux. MPL v1.1 [11] Tracker: Linux, Unix: Open-source desktop search tool for Unix/Linux GPL v2 [12] Tropes Zoom: Windows: Semantic Search Engine (no ...
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 ...
Say the search box is given two words.The search starts with two index lookups, and the two results are combined with a logical AND. But before they are displayed as search results, they must all be assigned a final score before the top twenty (listed on the first page) can be displayed, and they must be formatted with snippets and highlighting.
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.