Performance Study of N-grams in the Analysis of Sentiments
In this work, a study investigation was carried out using n-grams to classify sentiments with different machine learning and deep learning methods. We used this approach, which combines existing techniques, with the problem of predicting sequence tags to understand the advantages and problems confr...
Enregistré dans:
Auteurs principaux: | O. E. Ojo, A. Gelbukh, H. Calvo, O. O. Adebanji |
---|---|
Format: | article |
Langue: | EN |
Publié: |
Nigerian Society of Physical Sciences
2021
|
Sujets: | |
Accès en ligne: | https://doaj.org/article/c9218d7144f94c5d9b53e5401a12c6eb |
Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
-
Deep Learning-based Sentiment Analysis and Topic Modeling on Tourism During Covid-19 Pandemic
par: Ram Krishn Mishra, et autres
Publié: (2021) -
Weibo Text Sentiment Analysis Based on BERT and Deep Learning
par: Hongchan Li, et autres
Publié: (2021) -
Topic-Based Document-Level Sentiment Analysis Using Contextual Cues
par: Ciprian-Octavian Truică, et autres
Publié: (2021) -
Benchmarking Deep Learning Methods for Aspect Level Sentiment Classification
par: Tanu Sharma, et autres
Publié: (2021) -
Arabic Aspect-Based Sentiment Analysis: A Systematic Literature Review
par: Ruba Obiedat, et autres
Publié: (2021)