Recurrent Neural Network Based Boolean Factor Analysis and its Application to Word Clustering

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F09%3A00321649" target="_blank" >RIV/67985807:_____/09:00321649 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Recurrent Neural Network Based Boolean Factor Analysis and its Application to Word Clustering

Original language description

Neural network based algorithm for word clustering as an extension of the neural network based Boolean factor analysis algorithm is introduced. Technique based on a Bayesian procedure has been developed to provide a complete description of factors in terms of component probability and to enhance the accuracy of classification of documents. Method is applied to two types of textual data on Neural Networks in two different languages.

Czech name

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Czech description

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Type

J_x - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

CEP classification

BB - Applied statistics, operational research

OECD FORD branch

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Project

<a href="/en/project/1M0567" target="_blank" >1M0567: Centre for Applied Cybernetics</a><br>

Continuities

Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year

2009

Confidentiality

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

Name of the periodical

IEEE Transactions on Neural Networks

ISSN

1045-9227

e-ISSN

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Volume of the periodical

20

Issue of the periodical within the volume

7

Country of publishing house

US - UNITED STATES

Number of pages

14

Pages from-to

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UT code for WoS article

000267941800002

EID of the result in the Scopus database

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