Learning document representations using subspace multinomial model
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F16%3APU122424" target="_blank" >RIV/00216305:26230/16:PU122424 - isvavai.cz</a>
Result on the web
<a href="https://www.researchgate.net/publication/307889473_Learning_Document_Representations_Using_Subspace_Multinomial_Model" target="_blank" >https://www.researchgate.net/publication/307889473_Learning_Document_Representations_Using_Subspace_Multinomial_Model</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.21437/Interspeech.2016-1634" target="_blank" >10.21437/Interspeech.2016-1634</a>
Alternative languages
Result language
angličtina
Original language name
Learning document representations using subspace multinomial model
Original language description
Subspace multinomial model (SMM) is a log-linear model and can be used for learning low dimensional continuous representation for discrete data. SMMand its variants have been used for speaker verification based on prosodic features and phonotactic language recognition. In this paper, we propose a new variant of SMM that introduces sparsity and call the resulting model as `1 SMM. We show that `1 SMM can be used for learning document representations that are helpful in topic identification or classification and clustering tasks. Our experiments in document classification show that SMM achieves comparable results to models such as latent Dirichlet allocation and sparse topical coding, while having a useful property that the resulting document vectors are Gaussian distributed.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/LQ1602" target="_blank" >LQ1602: IT4Innovations excellence in science</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of Interspeech 2016
ISBN
978-1-5108-3313-5
ISSN
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e-ISSN
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Number of pages
5
Pages from-to
700-704
Publisher name
International Speech Communication Association
Place of publication
San Francisco
Event location
San Francisco
Event date
Sep 8, 2016
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000409394400145