Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Jianyun Shang"'
Publikováno v:
Frontiers in Neurorobotics, Vol 16 (2022)
Understanding human sentiment from their expressions is very important in human-robot interaction. But deep learning models are hard to represent grammatical changes for natural language processing (NLP), especially for sentimental analysis, which in
Externí odkaz:
https://doaj.org/article/a975613d3c354052a9162aa5c484aaa9
Autor:
Nada Boudjellal, Huaping Zhang, Asif Khan, Arshad Ahmad, Rashid Naseem, Jianyun Shang, Lin Dai
Publikováno v:
Complexity, Vol 2021 (2021)
The web is being loaded daily with a huge volume of data, mainly unstructured textual data, which increases the need for information extraction and NLP systems significantly. Named-entity recognition task is a key step towards efficiently understandi
Externí odkaz:
https://doaj.org/article/0e21feb03b784535bc9732d9fc69d248
Autor:
Asif Khan, Huaping Zhang, Nada Boudjellal, Arshad Ahmad, Jianyun Shang, Lin Dai, Bashir Hayat
Publikováno v:
Complexity, Vol 2021 (2021)
Context. Social media platforms such as Facebook and Twitter carry a big load of people’s opinions about politics and leaders, which makes them a good source of information for researchers to exploit different tasks that include election prediction
Externí odkaz:
https://doaj.org/article/de8838e2cac94a97a6edc307d616951e
Publikováno v:
Information Processing & Management. 60:103314
Publikováno v:
2022 International Conference on Industrial Automation, Robotics and Control Engineering (IARCE).
Publikováno v:
Natural Language Processing and Chinese Computing ISBN: 9783031171192
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3beb678e98012179868cee6597a6285b
https://doi.org/10.1007/978-3-031-17120-8_8
https://doi.org/10.1007/978-3-031-17120-8_8
Autor:
Asif Khan, Lin Dai, Nada Boudjellal, Arshad Ahmad, Huaping Zhang, Jianyun Shang, Rashid Naseem
Publikováno v:
Complexity, Vol 2021 (2021)
The web is being loaded daily with a huge volume of data, mainly unstructured textual data, which increases the need for information extraction and NLP systems significantly. Named-entity recognition task is a key step towards efficiently understandi
Publikováno v:
Scientific Programming, Vol 2020 (2020)
Politics is one of the hottest and most commonly mentioned and viewed topics on social media networks nowadays. Microblogging platforms like Twitter and Weibo are widely used by many politicians who have a huge number of followers and supporters on t
Publikováno v:
Advanced Data Mining and Applications ISBN: 9783030653897
ADMA
ADMA
Text classification is a fundamental task in natural language processing (NLP). Context semantics can greatly improve the accuracy of text classification tasks. Although there are some popular methods in obtaining semantics, current context semantic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a0ca6eb72d2afadcf481e0f6638e8e1d
https://doi.org/10.1007/978-3-030-65390-3_8
https://doi.org/10.1007/978-3-030-65390-3_8
Publikováno v:
2018 First Asian Conference on Affective Computing and Intelligent Interaction (ACII Asia).
An updated framework based on LDA is provided in this paper to extract features from online user reviews which are in Chinese. This model is an extension of the LDA by introducing the concepts of multi-gram and part of speech into it and it is named