Zobrazeno 1 - 10
of 46
pro vyhledávání: '"Angel Deborah S"'
Publikováno v:
Intelligent Data Analysis. 26:119-132
It is challenging for machine as well as humans to detect the presence of emotions such as sadness or disgust in a sentence without adequate knowledge about the context. Contextual emotion detection is a challenging problem in natural language proces
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2221d69fb1988664c8cbd349fa4301c2
https://doi.org/10.3233/ida-205587
https://doi.org/10.3233/ida-205587
Publikováno v:
2021 Fourth International Conference on Electrical, Computer and Communication Technologies (ICECCT).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6e47ed417e42a35b4173df95f5c844be
https://doi.org/10.1109/icecct52121.2021.9616710
https://doi.org/10.1109/icecct52121.2021.9616710
Autor:
Aviansh Gupta, Ayush Nanda, Mirnalinee Tt, Rajalakshmi Sivanaiah, Angel Deborah S, Abrit Pal Singh, S Milton Rajendram
Publikováno v:
SemEval@ACL/IJCNLP
This paper describes the system used for detecting humor in text. The system developed by the team TECHSSN uses binary classification techniques to classify the text. The data undergoes preprocessing and is given to ColBERT (Contextualized Late Inter
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a9f162857dbb708a198d56621c0ca3a9
https://doi.org/10.18653/v1/2021.semeval-1.167
https://doi.org/10.18653/v1/2021.semeval-1.167
Autor:
Micheal BERDINANTH, Samah SYED, Shudhesh VELUSAMY, Angel Deborah SUSEELAN, Rajalakshmi SIVANAIAH
Publikováno v:
Revista Română de Informatică și Automatică, Vol 34, Iss 1, Pp 23-30 (2024)
Considering the persistent challenge of early heart attack detection in patients, despite significant advancements in medical systems, this research project is motivated by the imperative need to develop effective predictive machine learning models.
Externí odkaz:
https://doaj.org/article/b782b8b7121d4a3fae6301a4ef2aba5e
Akademický článek
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Publikováno v:
SemEval@NAACL-HLT
Sentiment analysis plays an important role in E-commerce. Identifying ironic and sarcastic content in text plays a vital role in inferring the actual intention of the user, and is necessary to increase the accuracy of sentiment analysis. This paper d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::615c7ddecceb92ddbf752e57067a0709
https://doi.org/10.18653/v1/s18-1103
https://doi.org/10.18653/v1/s18-1103
Publikováno v:
International Journal of Computer Applications. 116:11-18
With the increase in consumption of energy and population, there is a grave need to conserve energy in every way possible. The inability to access and control the appliances from remote locations is one of the major reasons for energy loss. A web or
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0874ea23574bf98c300cdfbbb1f671fe
https://doi.org/10.5120/20379-2601
https://doi.org/10.5120/20379-2601
Publikováno v:
SemEval@ACL
The system developed by the SSN_MLRG1 team for Semeval-2017 task 5 on fine-grained sentiment analysis uses Multiple Kernel Gaussian Process for identifying the optimistic and pessimistic sentiments associated with companies and stocks. Since the comm
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e809d5da79e0218406d739b71b68d3f2
https://doi.org/10.18653/v1/s17-2139
https://doi.org/10.18653/v1/s17-2139
Publikováno v:
SemEval@ACL
The SSN MLRG1 team for Semeval-2017 task 4 has applied Gaussian Process, with bag of words feature vectors and fixed rule multi-kernel learning, for sentiment analysis of tweets. Since tweets on the same topic, made at different times, may exhibit di
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4427d1073ca7af7b68bda29969d6c642
https://doi.org/10.18653/v1/s17-2118
https://doi.org/10.18653/v1/s17-2118
Conference
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