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Grow up precision recall relationship curve in IR system using GP and fuzzy optimization in optimizing the user query

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F07%3A00021213" target="_blank" >RIV/61989100:27240/07:00021213 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Grow up precision recall relationship curve in IR system using GP and fuzzy optimization in optimizing the user query

  • Original language description

    An information retrieval (IR) system (IRs) (search engine) is said to be efficient, to the degree that always evaluates each object in the information base (database, document base, web,...) like the expert. The ability of IRs's is to retrieve mostly allrelevant objects (measured by the recall), and only the (most) relevant objects (measured by the precision) from the collection queried. Recall and precision measures provide the classical measure of the retrieval efficiency. They measure the degree towhich the query answer (the set of documents that retrieved by IRs as response to the user query). Where, the query answer is the set of relevant documents in the information based queried. Retrieving most relevant documents to the user query in IRs wasone of the most important methods of World Wide Web (WWW) search engines used in the world now.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/1ET100300414" target="_blank" >1ET100300414: Intelligent methods for incresing of reliability of electrical networks</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>Z - Vyzkumny zamer (s odkazem do CEZ)

Others

  • Publication year

    2007

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    NEURAL NETWORK WORLD

  • ISSN

    1210-0552

  • e-ISSN

  • Volume of the periodical

    17

  • Issue of the periodical within the volume

    4

  • Country of publishing house

    CZ - CZECH REPUBLIC

  • Number of pages

    15

  • Pages from-to

  • UT code for WoS article

    000249076100004

  • EID of the result in the Scopus database