Unsupervised Improving of Sentiment Analysis using Global Target Context
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F13%3A43919437" target="_blank" >RIV/49777513:23520/13:43919437 - isvavai.cz</a>
Result on the web
<a href="http://lml.bas.bg/ranlp2013/docs/RANLP_main.pdf" target="_blank" >http://lml.bas.bg/ranlp2013/docs/RANLP_main.pdf</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Unsupervised Improving of Sentiment Analysis using Global Target Context
Original language description
Current approaches to document-level sentiment analysis rely on local information, e.g., the words within the given document. We try to achieve better performance by incorporating global context of the sentiment target (e.g., a movie or a product). We assume that sentiment labels of reviews about the same target are often consistent in some way. We model this consistency by Dirichlet distribution over sentiment labels and use it together with Maximum entropy classifier to gain significant improvement. This unsupervised extension increases the classification F-measure by almost 3% absolute on both Czech and English movie review datasets and outperforms the current state of the art.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
<a href="/en/project/ED1.1.00%2F02.0090" target="_blank" >ED1.1.00/02.0090: NTIS - New Technologies for Information Society</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2013
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 Recent Advances in Natural Language Processing
ISBN
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ISSN
1313-8502
e-ISSN
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Number of pages
7
Pages from-to
122-128
Publisher name
Incoma Ltd.
Place of publication
Shoumen
Event location
Hissar
Event date
Sep 7, 2013
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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