Cargando…
Are GRU Cells More Specific and LSTM Cells More Sensitive in Motive Classification of Text?
In the Thematic Apperception Test, a picture story exercise (TAT/PSE; Heckhausen, 1963), it is assumed that unconscious motives can be detected in the text someone is telling about pictures shown in the test. Therefore, this text is classified by trained experts regarding evaluation rules. We tried...
Autores principales: | Gruber, Nicole, Jockisch, Alfred |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7861254/ https://www.ncbi.nlm.nih.gov/pubmed/33733157 http://dx.doi.org/10.3389/frai.2020.00040 |
Ejemplares similares
-
Research on sentiment classification for netizens based on the BERT-BiLSTM-TextCNN model
por: Jiang, Xuchu, et al.
Publicado: (2022) -
Deepfake tweets classification using stacked Bi-LSTM and words embedding
por: Rupapara, Vaibhav, et al.
Publicado: (2021) -
A GRU-based traffic situation prediction method in multi-domain software defined network
por: Sun, Wenwen, et al.
Publicado: (2022) -
LSTM-based sentiment analysis for stock price forecast
por: Ko, Ching-Ru, et al.
Publicado: (2021) -
Event classification from the Urdu language text on social media
por: Awan, Malik Daler Ali, et al.
Publicado: (2021)