FAST SUPERVISED FEATURE EXTRACTION FROM STRUCTURED REPRESENTATION OF TEXT DATA

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F10%3A00171783" target="_blank" >RIV/68407700:21230/10:00171783 - isvavai.cz</a>
Alternative codes found
RIV/68407700:21240/10:00171783
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
FAST SUPERVISED FEATURE EXTRACTION FROM STRUCTURED REPRESENTATION OF TEXT DATA
Original language description
Classification of text documents is challenging problem not only when browsing the web. Structure representation of documents is necessary to build up appropriate classifier. Unfortunately the document-term matrices are usually so sparse and of high dimensionality due large number of terms representing usually smaller number of the documents. Thus the suitable dimensionality reduction technique is required to be able to develop the classifier. The article deals with supervised extraction method that results to small number of sensitive features derived from the initial document-term matrix. The extraction process simulated by neural network is remarkably fast and utilizes all available supervised information from training data.
Czech name
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Czech description
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Project
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Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)<br>S - Specificky vyzkum na vysokych skolach

Publication year
2010
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the 7th EUROSIM Congress on Modelling and Simulation, Vol. 2: Full Papers
ISBN
978-80-01-04589-3
ISSN
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e-ISSN
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Number of pages
7
Pages from-to
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Publisher name
Department of Computer Science and Engineering, FEE, CTU in Prague
Place of publication
Prague
Event location
Praha
Event date
Sep 6, 2010
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
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