A Survey on Machine Learning and Deep Learning Based Approaches for Sarcasm Identification in Social Media

Shah, Bhumi; Shah, Margil

doi:10.1007/978-981-15-4474-3_29

Search citation statements

Order By: Relevance

Paper Sections

Select...

Introduction1

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2021

2024

Publication Types

Select...

Article4

Other1

Relationship

Self Cite0

Independent5

Authors

Journals

Cited by 5 publications

(1 citation statement)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the study developed by [10], applied using neural network, data mining and decision trees whose target was the identification and prediction among the variables related to socioeconomic and academic information obtained across the skill Extract, Transform and Load (ETL).…”

Section: Introductionmentioning

confidence: 99%

Deep Neural Network DNN Applied to the Analysis of Student Dropout

Barón

Sanabria²,

Diaz³

2022

Investigación e Innovación en Ingenierías

View full text Add to dashboard Cite

This paper reports the design of a deep neural network (DNN) focused to predict patterns of student dropout at the UPTC University of Colombia. We apply specialized artificial intelligence (AI) algorithms for the implementation of the DNN specifically were using a learning machine for classification and clustering task. Additionally, a dataset containing 17 attributes of 3000 academically active students was structured; the data set has been prepared to be trained as an entry to the neural network. The final result of the research reveals a predictive model trained through the DNN validated by several quality metrics that demonstrate reliability and accuracy of the results accomplished through the model.

show abstract

Section: Introductionmentioning

confidence: 99%