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
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DOI - Digital Object Identifier
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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
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Czech description
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Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
IN - Informatics
OECD FORD branch
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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
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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
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UT code for WoS article
000249076100004
EID of the result in the Scopus database
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