Zobrazeno 1 - 10
of 76
pro vyhledávání: '"Cina Motamed"'
Autor:
Meysam Asgari-Chenaghlu, Mohammad-Reza Feizi-Derakhshi, Leili Farzinvash, Mohammad-Ali Balafar, Cina Motamed
Publikováno v:
Complexity, Vol 2021 (2021)
Social networks are real-time platforms formed by users involving conversations and interactions. This phenomenon of the new information era results in a very huge amount of data in different forms and modalities such as text, images, videos, and voi
Externí odkaz:
https://doaj.org/article/3dd1232c7c58408bb37352984b904e43
Publikováno v:
Annals of computer science and information systems, Vol 8, Pp 477-482 (2016)
Externí odkaz:
https://doaj.org/article/8395f57ff0124f3a8e0ba13088b08b28
Autor:
M. Reza Feizi-Derakhshi, Meysam Asgari-Chenaghlu, Leili Farzinvash, Cina Motamed, Mohammad Ali Balafar
Publikováno v:
Neural Computing and Applications. 34:1905-1922
Named entity recognition (NER) from social media posts is a challenging task. User-generated content that forms the nature of social media is noisy and contains grammatical and linguistic errors. This noisy content makes tasks such as NER much harder
Publikováno v:
Applied Intelligence.
Publikováno v:
SSRN Electronic Journal.
Autor:
Cina Motamed, Leili Farzinvash, Mohammad Ali Balafar, Meysam Asgari-Chenaghlu, Mohammad-Reza Feizi-Derakhshi
Publikováno v:
Complexity, Vol 2021 (2021)
Social networks are real-time platforms formed by users involving conversations and interactions. This phenomenon of the new information era results in a very huge amount of data in different forms and modalities such as text, images, videos, and voi
Autor:
Meysam Asgari-Chenaghlu, Mohammad Reza Feizi Derakhshi, Leili Farzinvash, Balafar, M. A., Cina Motamed
Publikováno v:
Web of Science
Named Entity Recognition (NER) from social media posts is a challenging task. User generated content that forms the nature of social media, is noisy and contains grammatical and linguistic errors. This noisy content makes it much harder for tasks suc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4c3824094e37ffaedc025a92514bd253
http://arxiv.org/abs/2001.06888
http://arxiv.org/abs/2001.06888
Publikováno v:
ICPRAM
Publikováno v:
ICINCO
Publikováno v:
Chaos, Solitons & Fractals. 153:111494
The fuzzy k-modes (FKM) is a popular method for clustering categorical data. However, the main problem of this algorithm is that it is very sensitive to the initialization of primary clusters, so inappropriate initial cluster centers lead to poor loc