Adam Deep Learning With SOM for Human Sentiment Classification

Md. Nawab Yousuf Ali, Md. Golam Sarowar, Md. Lizur Rahman, Jyotismita Chaki, Nilanjan Dey and João Manuel R.S. Tavares
Additional contact information
Md. Nawab Yousuf Ali: Department of Computer Science and Engineering, East West University, Dhaka, Bangladesh
Md. Golam Sarowar: East West University, Dhaka, Bangladesh
Md. Lizur Rahman: East West University, Dhaka, Bangladesh
Jyotismita Chaki: Vellore Institute of Technology, Vellore, India
Nilanjan Dey: Department of Information Technology, Techno India College of Technology, Kolkata, India
João Manuel R.S. Tavares: Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial, Departamento de Engenharia Mecânica, Faculdade de Engenharia, Universidade do Porto, Porto, Portugal

International Journal of Ambient Computing and Intelligence (IJACI), 2019, vol. 10, issue 3, 92-116

Abstract: Nowadays, with the improvement in communication through social network services, a massive amount of data is being generated from user's perceptions, emotions, posts, comments, reactions, etc., and extracting significant information from those massive data, like sentiment, has become one of the complex and convoluted tasks. On other hand, traditional Natural Language Processing (NLP) approaches are less feasible to be applied and therefore, this research work proposes an approach by integrating unsupervised machine learning (Self-Organizing Map), dimensionality reduction (Principal Component Analysis) and computational classification (Adam Deep Learning) to overcome the problem. Moreover, for further clarification, a comparative study between various well known approaches and the proposed approach was conducted. The proposed approach was also used in different sizes of social network data sets to verify its superior efficient and feasibility, mainly in the case of Big Data. Overall, the experiments and their analysis suggest that the proposed approach is very promissing.

Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 018/IJACI.2019070106 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jaci00:v:10:y:2019:i:3:p:92-116

Access Statistics for this article

International Journal of Ambient Computing and Intelligence (IJACI) is currently edited by Nilanjan Dey

More articles in International Journal of Ambient Computing and Intelligence (IJACI) from IGI Global
Bibliographic data for series maintained by Journal Editor ().