Application of Finite Mixtures to Text Document Classification

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F03%3A03076944" target="_blank" >RIV/68407700:21230/03:03076944 - isvavai.cz</a>
Alternative codes found
RIV/67985556:_____/03:16030020
Result on the web
—
DOI - Digital Object Identifier
—

Result language
angličtina
Original language name
Application of Finite Mixtures to Text Document Classification
Original language description
Finite mixture modelling of class-conditional distributions is a standard method in a statistical pattern recognition. We proposed to use the mixture of multinomial distributions as a model for class-conditional distribution for text document classification task. The vector document representations using a bag-of-words or a unigram approach are employed.Experimental comparison of the proposed model and the standard Bernoulli and multinomial models as well as the model based on mixture of multivariate Bernoulli distributions was performed using Reuters-21578 database. Preliminary experimental results indicate the effectiveness of proposed model based on mixture of multinomial distributions in a text classification task.
Czech name
—
Czech description
—

Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year
2003
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Znalosti 2003 - sborník příspěvků 2. ročníku konference
ISBN
80-248-0229-5
ISSN
—
e-ISSN
—
Number of pages
10
Pages from-to
23-32
Publisher name
VŠB-TUO
Place of publication
Ostrava
Event location
Ostrava
Event date
Feb 19, 2003
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
—

Similar results(10)