Please use this identifier to cite or link to this item:
Author(s): Md. Nawab Yousuf Ali
Md. Golam Sarowar
Md. Lizur Rahman
Jyotismita Chaki
Nilanjan Dey
João Manuel R. S. Tavares
Title: Adam Deep Learning with SOM for Human Sentiment Classification
Issue Date: 2019-07
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.
Subject: Ciências Tecnológicas, Ciências da engenharia e tecnologias
Technological sciences, Engineering and technology
Scientific areas: Ciências da engenharia e tecnologias
Engineering and technology
Document Type: Artigo em Revista Científica Internacional
Rights: openAccess
Appears in Collections:FEUP - Artigo em Revista Científica Internacional

Files in This Item:
File Description SizeFormat 
367869.1.pdfPaper draft2.11 MBAdobe PDFThumbnail
367869.jpg1st Page364.95 kBJPEGThumbnail

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.