Email this article Sentiment Analysis Using Hybrid Approach
Abstract
Sentiment Analysis, also known as opinion mining, focuses on the use of techniques that can automatically recognize various forms of emotions conveyed in a text, such as sentiments, attitudes, and views. Sentiment Analysis is a field of text mining that is still being researched. This review study provides insights into numerous suggested Sentiment Analysis algorithms as well as a quick overview of the most recent developments in this subject. This study also covers data science-related topics such as emotion recognition and building resources. This paper primarily offers a sophisticated classification of various papers as well as a quick introduction to the recent trend of research in this subject.
Keywords
Full Text:
PDFReferences
S. A. Bini, “Artificial Intelligence, Machine Learning, Deep Learning, and Cognitive Computing: What Do These Terms Mean and How Will They Impact Health Care?” J. Arthroplasty, vol. 33, no. 8, pp. 2358–2361, 2018, doi: 10.1016/j.arth.2018.02.067.
A. S. Sultan, M. A. Elgharib, T. Tavares, M. Jessri, and J. R. Basile, “The use of artificial intelligence, machine learning and deep learning in oncologic histopathology,” J. Oral Pathol. Med., vol. 49, no. 9, pp. 849–856, 2020, doi: 10.1111/jop.13042.
P. P. Shinde and S. Shah, “A Review of Machine Learning and Deep Learning Applications,” Proc. - 2018 4th Int. Conf. Comput. Commun. Control Autom. ICCUBEA 2018, pp. 1–6, 2018, doi: 10.1109/IC- CUBEA.2018.8697857.
Q. Bi, K. E. Goodman, J. Kaminsky, and J. Lessler, “What is machine learning? A primer for the epidemiologist,” Am. J. Epidemiol., vol. 188, no. 12, pp. 2222–2239, 2019, doi: 10.1093/aje/kwz189.
J. Yu et al., “Noninvasive IDH1 mutation estimation based on a quantitative radiomics approach for grade II glioma,” Eur. Radiol., vol. 27, no. 8, pp. 3509–3522, 2017, doi: 10.1007/s00330-016-4653-3.
R. Chen and M. Snyder, “Promise of personalized omics to precision medicine,” Wiley Interdiscip. Rev. Syst. Biol. Med., vol. 5, no. 1, pp. 73–82, 2013, doi: 10.1002/wsbm.1198.
Rui Ha, Pengyu Liu and Kebin Jia, "An Improved Adaptive Median Filter Algorithm and Its Application", International conference in Advances in Intelligent Information Hiding and Multimedia Signal Processing, 2016.
Madhu S. Nair , P. M. Ameera Mol, "An Efficient Adaptive Weighted Switching Median Filter for Removing High Density Impulse Noise", Springer ,J. Inst. Eng. India, 95(3):255–278, 2014.
Duan F, Zhang Y-J,”A Highly effective impulse noise detection algorithm for switching median filters”, IEEE Signal Process. Lett., 17(7), pp. 647–650, 2010.
L. E. Rossovskii, "Image Filtering with the Use of anisotropic diffusion",ISSN 0965-5425, Computational Mathematics and Mathematical Physics,Vol. 57, No. 3, pp. 401–408, 2017.
Resmi R. Nair, Ebenezer David and Sivakumar Raja gopal, "A robust anisotropic diffusion filter with low arithmetic complexity for images", EURASIP Journal on Image and Video Processing, vol-48, 2019.
M. Hanmandlu, D.V. Ramona Murthy Vamsi Krishna Madasu, "Fuzzy Model based recognition of handwritten Hindi characters", International Conference on Computer and Information Science (ICIS 2007) 0-7695-2841-4,IEEE 2007.
Akanksha Gaur, Sunita Yadav, "Handwritten Hindi character recognition using K Means clustering and SVM", International Symposium on Emerging Trends and Technologies in Libraries and Information Services, pp. 65-70,IEEE 2015.
Nikita Singh, "An Efficient Approach for handwritten devanagari character recognition based on Artificial Neural Network", IEEE 2018.
Whig, P., & Ahmad, S. (2019). Methodology for Calibrating Photocatalytic Sensor Output. International Journal of Sustainable Development in Computing Science, 1(1), 1-10. Retrieved from https://ijsdcs.com/index.php/ijsdcs/article/view/4
Pawan Whig and S. N Ahmad, “CMOS Integrated VDBA-ISFET Device for Water Quality Monitoring, International journal of intelligent engineering and systems, accepted for publication 2014,Vol.7, No.1,2014. (Scopus) ISSN: 2185-3118
Pawan Whig and Vaibhav Bhatia,” Performance Analysis of Multi-Functional Bot System Design Using Microcontroller” International Journal of Intelligent Systems and Applications,2014 ,02 pp 69-75.ISSN No: 2074-9058
Pawan Whig and S. N. Ahmad, “Development of Low Power Dynamic Threshold PCS System”, Journal of Electrical and Electronic Systems,2014, Vol. 3, Issue3, pp. 1-6. ISSN No:2332-0796
Pawan Whig and S. N. Ahmad, “Novel FGMOS Based PCS Device for Low Power Applications ”,Photonic Sensor(Springer), 2015,Vol.5,Issue 2, pp 1-5.(SCI, ISI Index) ISSN No: 1674-9251
Pawan Whig and S. N. Ahmad,“Impact of Parameters on characteristic of Novel PCS” ,Canadian journal of Basic and applied Science, 2015 , Vol.3, Issue2,pp 45-52. ISSN No: 2292-3381
Ruchin, Chandan Mahto and Pawan Whig,” Design and Simulation of Dynamic UART Using Scan Path Technique (USPT)", International Journal of Electrical, Electronics & Computer Science Engineering” 2015,Vol 1, pp 6-11. ISSN No: 2348-2273
Aastha Sharma, Abhishek Kumar, Pawan Whig,” On the performance of CDTA based novel analog inverse low pass filter using 0.35µm CMOS parameter”, International Journal of Science, Technology & Management, 2015, Vol 4, Issue 1, pp. 594-601. ISSN No: 1460-6720
Pawan Whig and S. N Ahmad,” Simulation and Performance Analysis of Low Power Quasi Floating Gate PCS Model ”, International Journal of Intelligent Engineering and Systems, 2016, Vol 9, Issue 2, pp. 8-13(Scopus). ISSN: 2185-3118
Pawan Whig and S. N Ahmad ,” Ultraviolet Photo Catalytic Oxidation (UVPCO) Sensor for Air and Surface Sanitizers Using CS amplifier”, global Journal of researches in engineering: F 2016, Vol. 16, Issue 6, pp.1-13. ISSN Numbers: Online: 2249-4596 Print: 0975-5861 DOI: 10.17406/GJRE
Arrese A and Albarran AB (2003) Time and media markets: Summary and research agenda. In: Albarran AB and Arrese A (eds) Time and Media Markets. London: Lawrence Erlbaum Associates Publishers, pp. 161–171.
Jiwani, N., & Gupta, K. (2019). Comparison of Various Tools and Techniques used for Project Risk Management. International Journal of Machine Learning for Sustainable Development, 1(1), 51-58.
Refbacks
- There are currently no refbacks.
Copyright (c) 2021 International Journal of Machine Learning for Sustainable Development
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Impact Factor :
JCR Impact Factor: 5.9 (2020)
JCR Impact Factor: 6.1 (2021)
JCR Impact Factor: 6.7 (2022)
JCR Impact Factor: 7.6 (2023)
JCR Impact Factor: 8.6 (2024)
JCR Impact Factor: Under Evaluation (2025)
A Double-Blind Peer-Reviewed Refereed Journal