scholarly journals The Impact of Arabic Part of Speech Tagging on Sentiment Analysis: A New Corpus and Deep Learning Approach

2021 ◽  
Vol 184 ◽  
pp. 148-155
Author(s):  
Abdul Munem Nerabie ◽  
Manar AlKhatib ◽  
Sujith Samuel Mathew ◽  
May El Barachi ◽  
Farhad Oroumchian
Keyword(s):  
Deep Learning ◽  
Sentiment Analysis ◽  
Learning Approach ◽  
Part Of Speech Tagging ◽  
Part Of Speech ◽  
The Impact ◽  
Speech Tagging

scholarly journals Part of Speech Tagging in Urdu: Comparison of Machine and Deep Learning Approaches

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 38918-38936 ◽  
Author(s):  
Wahab Khan ◽  
Ali Daud ◽  
Khairullah Khan ◽  
Jamal Abdul Nasir ◽  
Mohammed Basheri ◽  
...  
Keyword(s):  
Deep Learning ◽  
Learning Approaches ◽  
Part Of Speech Tagging ◽  
Part Of Speech ◽  
Speech Tagging

scholarly journals To Batch or Not to Batch? Comparing Batching and Curriculum Learning Strategies across Tasks and Datasets

Mathematics ◽  
2021 ◽  
Vol 9 (18) ◽  
pp. 2234
Author(s):  
Laura Burdick ◽  
Jonathan K. Kummerfeld ◽  
Rada Mihalcea
Keyword(s):  
Learning Strategies ◽  
Language Processing ◽  
Training Data ◽  
Systematic Analysis ◽  
Part Of Speech Tagging ◽  
Part Of Speech ◽  
Multiple Datasets ◽  
Processing Architectures ◽  
The Impact ◽  
Speech Tagging

Many natural language processing architectures are greatly affected by seemingly small design decisions, such as batching and curriculum learning (how the training data are ordered during training). In order to better understand the impact of these decisions, we present a systematic analysis of different curriculum learning strategies and different batching strategies. We consider multiple datasets for three tasks: text classification, sentence and phrase similarity, and part-of-speech tagging. Our experiments demonstrate that certain curriculum learning and batching decisions do increase performance substantially for some tasks.

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