Mixture Models for Learning Text Document Classifiers
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F03%3A03092961" target="_blank" >RIV/68407700:21230/03:03092961 - 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
Mixture Models for Learning Text Document Classifiers
Original language description
The goal of text document classification is to assign a new document into one class from the predefined classes based on its contents. In this paper, a mixture of multinomial distributions is proposed as a model for class-conditional distributions in document classification task.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
JC - Computer hardware and software
OECD FORD branch
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Result continuities
Project
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Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)
Others
Publication year
2003
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Information Technologies and Control
ISBN
80-239-1333-6
ISSN
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e-ISSN
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Number of pages
1
Pages from-to
6-6
Publisher name
ÚTIA
Place of publication
Praha
Event location
Libverda
Event date
Sep 16, 2003
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
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