Active learning enhanced semi-automatic annotation tool for aspect-based sentiment analysis

Smatana, Miroslav; Koncz, P.; Smatana, Peter; Paralič, Ján

doi:10.1109/sisy.2013.6662568

Cited by 6 publications

(1 citation statement)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It only takes 190 sentences using active learning to get the same quality of 270 sentences without using active learning. Sentiment accuracy for both annotation tools was also measured, where the accuracy of the active learning annotation tool increased by more than 60% and the accuracy of the annotation tool without active learning was about 57% [14].…”

Section: Figure 2 Accuracy Results Of Libnear and Mnbmentioning

confidence: 99%

A Literature Research on Machine Learning Techniques used for Training Annotated Corpus

2019

IJRTE

View full text Add to dashboard Cite

The development of research in the annotation area is growing. Researchers perform annotation task using various forms of datasets such as text, sound, images, and videos. Various algorithms are used to perform tasks. The purpose of this survey is to find out algorithms that are often used by researchers to perform annotation tasks, especially on text data. The literature surveys thirteen research papers on text annotation from the last 5 years. The results of this review indicate that SVM is the algorithm used for all three annotation methods: manual, automatic and semi-automatic annotation, with a significant accuracy above 80%. The result of this survey will be referred by the authors as the basis for subsequent research that will be conducted, especially in the semi-automatic annotation method.

show abstract

Section: Figure 2 Accuracy Results Of Libnear and Mnbmentioning

confidence: 99%

A Literature Research on Machine Learning Techniques used for Training Annotated Corpus

2019

IJRTE

View full text Add to dashboard Cite

show abstract

Machine Learning-Based Sentiment Analysis for Analyzing the Travelers Reviews on Egyptian Hotels

Mostafa

2020

Advances in Intelligent Systems and Computing

View full text Add to dashboard Cite

Understating Factors Affecting Traveling During COVID-19 Using Sentiment Analysis

Mostafa

Beshir

2021

Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2021

View full text Add to dashboard Cite

Active learning enhanced semi-automatic annotation tool for aspect-based sentiment analysis

Cited by 6 publications

References 13 publications

A Literature Research on Machine Learning Techniques used for Training Annotated Corpus

A Literature Research on Machine Learning Techniques used for Training Annotated Corpus

Machine Learning-Based Sentiment Analysis for Analyzing the Travelers Reviews on Egyptian Hotels

Understating Factors Affecting Traveling During COVID-19 Using Sentiment Analysis

Contact Info

Product

Resources

About