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A New Opinion Mining Method based on Fuzzy Classifier and Particle Swarm Optimization (PSO) Algorithm Cover

A New Opinion Mining Method based on Fuzzy Classifier and Particle Swarm Optimization (PSO) Algorithm

Open Access
|Jun 2018

References

  1. 1. Ravi, K., V. Ravi. A Survey on Opinion Mining and Sentiment Analysis: Tasks, Approaches and Applications. – Knowledge-Based Systems, Vol. 89, 2015, pp. 14-46.10.1016/j.knosys.2015.06.015
  2. 2. Balazs, J. A., J. D. Velásquez. Opinion Mining and Information Fusion: A Survey. – Information Fusion, Vol. 27, 2016, pp. 95-110.10.1016/j.inffus.2015.06.002
  3. 3. Basari, A. S. H., B. Hussin, I. G. P. Ananta, J. Zeniarja. Opinion Mining of Movie Review Using Hybrid Method of Support Vector Machine and Particle Swarm Optimization. – Procedia Engineering, Vol. 53, 2013, pp. 453-462.10.1016/j.proeng.2013.02.059
  4. 4. Ye, Q., Z. Zhang, R. Law. Sentiment Classification of Online Reviews to Travel Destinations by Supervised Machine Learning Approaches. – Expert Systems with Applications, Vol. 36, 2009, No 3, pp. 6527-6535.10.1016/j.eswa.2008.07.035
  5. 5. Virmani, D., V. Malhotra, R. Tyagi. Sentiment Analysis Using Collaborated Opinion Mining. – arXiv preprint arXiv:1401.2618., 2014.
  6. 6. Zadeh, L. A. Fuzzy Sets. – Information and Control, Vol. 8, 1965, No 3, pp. 338-353.10.1016/S0019-9958(65)90241-X
  7. 7. Jebaseeli, A. N., E. Kirubakaran. Genetic Optimized Neural Network Algorithm to Improve Classification Accuracy for Opinion Mining of m-Learning Reviews. – IJETTCS, Vol. 2, 2013, No 3, pp. 345-349.
  8. 8. Jusoh, S., H. M. Alfawareh. Applying Fuzzy Sets for Opinion Mining. – In: IEEE International Conference on Computer Applications Technology (ICCAT’13), 2013, pp. 1-5.10.1109/ICCAT.2013.6521965
  9. 9. Bagheri, A., M. Saraee, F. de Jong. An Unsupervised Aspect Detection Model for Sentiment Analysis of Reviews. – In: International Conference on Application of Natural Language to Information Systems. Berlin, Heidelberg, Springer, 2013, pp. 140-151.10.1007/978-3-642-38824-8_12
  10. 10. Stylios, G., C. D. Katsis, D. Christodoulakis. Using Bio-Inspired Intelligence for Web Opinion Mining. – International Journal of Computer Applications, Vol. 87, 2014, No 5.10.5120/15207-3610
  11. 11. Kalaivani, P., K. L. Shunmuganathan. An Improved k-Nearest-Neighbor Algorithm Using Genetic Algorithm for Sentiment Classification. – In: 2014 IEEE International Conference on Circuit, Power and Computing Technologies (ICCPCT’14), March 2014, pp. 1647-1651.10.1109/ICCPCT.2014.7054826
  12. 12. Dalal, M. K., M. A. Zaveri. Opinion Mining from Online User Reviews Using Fuzzy Linguistic Hedges. – Applied Computational Intelligence and Soft Computing, 2014, No 2.10.1155/2014/735942
  13. 13. Sumathi, T., S. Karthik, M. Marikkannan. Artificial Bee Colony Optimization for Feature Selection in Opinion Mining. – Journal of Theoretical & Applied Information Technology, Vol. 66, 2014, No 1.
  14. 14. Rahmath, P., T. Ahmad. Fuzzy Based Sentiment Analysis of Online Product Reviews Using Machine Learning Techniques. – International Journal of Computer Applications, Vol. 99, 2014, No 17, pp. 9-16.10.5120/17463-8243
  15. 15. Kalaivani, P., K. L. Shunmuganathan. Feature Reduction Based on Genetic Algorithm and Hybrid Model for Opinion Mining. – Scientific Programming, Vol. 12, 2015.10.1155/2015/961454
  16. 16. Bilal, M., H. Israr, M. Shahid, A. Khan. Sentiment Classification of Roman-Urdu Opinions Using Naïve Bayesian, Decision Tree and k-NN Classification Techniques. – Journal of King Saud University-Computer and Information Sciences, Vol. 28, 2016, No 3, pp. 330-344.10.1016/j.jksuci.2015.11.003
  17. 17. Bagheri, A., M. Saraee, F. de Jong. ADM-LDA: An Aspect Detection Model Based on Topic Modelling Using the Structure of Review Sentences. – Journal of Information Science, Vol. 40, 2014, No 5, pp. 621-636.10.1177/0165551514538744
  18. 18. Chawla, N. V., K. W. Bowyer, L. O. Hall, W. P. Kegelmeyer. SMOTE: Synthetic Minority Over-Sampling Technique. – Journal of Artificial Intelligence Research, Vol. 16, 2002, pp. 321-357.10.1613/jair.953
  19. 19. Mendel, J. M. Uncertain Rule-Based Fuzzy Logic Systems: Introduction and New Directions. Upper Saddle River, Prentice Hall PTR, 2001, pp. 131-184.
  20. 20. Ishibuchi, H., Y. Nojima. Pattern Classification with Linguistic Rules. – In: Fuzzy Sets and Their Extensions: Representation, Aggregation and Models, 2008, pp. 377-395.10.1007/978-3-540-73723-0_19
DOI: https://doi.org/10.2478/cait-2018-0026 | Journal eISSN: 1314-4081 | Journal ISSN: 1311-9702
Language: English
Page range: 36 - 50
Submitted on: Nov 25, 2017
Accepted on: Feb 15, 2018
Published on: Jun 30, 2018
Published by: Bulgarian Academy of Sciences, Institute of Information and Communication Technologies
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2018 Samira Bordbar, Pirooz Shamsinejad, published by Bulgarian Academy of Sciences, Institute of Information and Communication Technologies
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.