Twitter Part-Of-Speech Tagging Using Pre-classification Hidden Markov Model
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F12%3A86084785" target="_blank" >RIV/61989100:27240/12:86084785 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/ICSMC.2012.6377881" target="_blank" >http://dx.doi.org/10.1109/ICSMC.2012.6377881</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICSMC.2012.6377881" target="_blank" >10.1109/ICSMC.2012.6377881</a>
Alternative languages
Result language
angličtina
Original language name
Twitter Part-Of-Speech Tagging Using Pre-classification Hidden Markov Model
Original language description
Hidden Markov models (HMM) have been widely used in natural language processing (NLP), especially in syntactic level applications, which appears naturally as short-range-dependent sequence recognition problems. But the structure of HMM limits the usage of global knowledge including the sentiment analysis of the text, which has become an increasingly popular research topic in NLP now. In this paper, we propose a novel treatment of HMM model to use the result of sentimental subjectivity analysis in syntactic level task, i.e. part-of-speech (POS) tagging. The subjectivity information is introduced as a pre-classification procedure into the interval-type HMM. The subjectivity degree of the testing sentence is used as a combination factor to choose an appropriate value from the interval. Experiments results on public tagging data sets shows that the proposed approach enhanced the performance of POS tagging.
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/EE.2.3.20.0073" target="_blank" >EE.2.3.20.0073: Bio-Inspired Methods: research, development and knowledge transfer</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
2012
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics 2012
ISBN
978-1-4673-1714-6
ISSN
1062-922X
e-ISSN
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Number of pages
6
Pages from-to
1118-1123
Publisher name
IEEE
Place of publication
New York
Event location
Soul
Event date
Oct 14, 2012
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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