Cargando…
SentiMedQAer: A Transfer Learning-Based Sentiment-Aware Model for Biomedical Question Answering
Recent advances have witnessed a trending application of transfer learning in a broad spectrum of natural language processing (NLP) tasks, including question answering (QA). Transfer learning allows a model to inherit domain knowledge obtained from an existing model that has been sufficiently pre-tr...
Autores principales: | Zhu, Xian, Chen, Yuanyuan, Gu, Yueming, Xiao, Zhifeng |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8961296/ https://www.ncbi.nlm.nih.gov/pubmed/35360832 http://dx.doi.org/10.3389/fnbot.2022.773329 |
Ejemplares similares
-
SentiInc: Incorporating Sentiment Information into Sentiment Transfer Without Parallel Data
por: Pant, Kartikey, et al.
Publicado: (2020) -
SentiHealth: creating health-related sentiment lexicon using hybrid approach
por: Asghar, Muhammad Zubair, et al.
Publicado: (2016) -
Malay sentiment analysis based on combined classification approaches and Senti-lexicon algorithm
por: Al-Saffar, Ahmed, et al.
Publicado: (2018) -
RuSentiTweet: a sentiment analysis dataset of general domain tweets in Russian
por: Smetanin, Sergey
Publicado: (2022) -
SentiTAM: Sentiments centered integrated framework for mobile learning adaptability in higher education
por: Qazi, Atika, et al.
Publicado: (2022)