Zobrazeno 1 - 10
of 49
pro vyhledávání: '"Shad Akhtar"'
Publikováno v:
Humanities & Social Sciences Communications, Vol 11, Iss 1, Pp 1-12 (2024)
Abstract The advent of globalization and adaptation to multiple cultures has emanated a fusion of Hindi and English, casually known as Hinglish. The phenomenon of mixing multiple languages (such as Hindi and English) within a single utterance is ofte
Externí odkaz:
https://doaj.org/article/dd04d2643250465bb49e5749ec007773
Publikováno v:
IEEE Transactions on Computational Social Systems. :1-11
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9bdff89503ed1198c8707b99520b254e
https://doi.org/10.1109/tcss.2023.3244014
https://doi.org/10.1109/tcss.2023.3244014
Publikováno v:
Proceedings of the ACM Web Conference 2023.
Virtual Mental Health Assistants (VMHAs) have become a prevalent method for receiving mental health counseling in the digital healthcare space. An assistive counseling conversation commences with natural open-ended topics to familiarize the client wi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0bdbd5c006eaec74d505a18fe1517b60
https://doi.org/10.1145/3543507.3583380
https://doi.org/10.1145/3543507.3583380
Publikováno v:
IEEE Transactions on Affective Computing. 13:285-297
We propose a multi-task ensemble framework that jointly learns multiple related problems. The ensemble model aims to leverage the learned representations of three deep learning models (i.e., CNN, LSTM and GRU) and a hand-crafted feature representatio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::35c9d16dcc19eade11b32b4414e52680
https://doi.org/10.1109/taffc.2019.2926724
https://doi.org/10.1109/taffc.2019.2926724
Publikováno v:
Computational Linguistics and Intelligent Text Processing ISBN: 9783031243394
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::152f9305fd0d5d0245570fc103e52483
https://doi.org/10.1007/978-3-031-24340-0_18
https://doi.org/10.1007/978-3-031-24340-0_18
Publikováno v:
IEEE Transactions on Computational Social Systems. 8:1323-1332
In this article, we address the problem of data scarcity for the sequence classification tasks. We propose AugmentGAN, a simple-yet-effective generative adversarial network-based text augmentation model, which ensures syntactic coherency in the newly
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::540663fe74587a9374ff4b9fb1b30bf6
https://doi.org/10.1109/tcss.2021.3075774
https://doi.org/10.1109/tcss.2021.3075774
Publikováno v:
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6beaf97180fed0abecf48f91d98f271d
https://doi.org/10.1145/3534678.3539187
https://doi.org/10.1145/3534678.3539187
Autor:
Usha Lokala, Aseem Srivastava, Triyasha Ghosh Dastidar, Tanmoy Chakraborty, Md Shad Akhtar, Maryam Panahiazar, Amit Sheth
Analyzing gender is critical to study mental health (MH) support in CVD (cardiovascular disease). The existing studies on using social media for extracting MH symptoms consider symptom detection and tend to ignore user context, disease, or gender. Th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::420d6ee8096ba91c02d5b8b3dbf7bb54
http://arxiv.org/abs/2203.11856
http://arxiv.org/abs/2203.11856
Akademický článek
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Publikováno v:
Neurocomputing. 398:247-256
Aspect sentiment classification has a dependency over the aspect term extraction. The majority of the existing studies tackle these two problems independently, i.e., while performing aspect sentiment classification, it is assumed that the aspect term
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1695ea0c06d8104a77df58eab1968a03
https://doi.org/10.1016/j.neucom.2020.02.093
https://doi.org/10.1016/j.neucom.2020.02.093