THE CLASSIFICATION OF CUSTOMERS SENTIMENT USING DATA MINING APPROACHES

http://dx.doi.org/10.31703/gssr.2019(IV-IV).19      10.31703/gssr.2019(IV-IV).19      Published : Dec 2019
Authored by : Dost Muhammad Khan , Tariq Aziz Rao , Faisal Shahzad

19 Pages : 146-156

References

  • Ahmad, M., S. Aftab & I. Ali. (2017). Sentiment Analysis of Tweets using SVM. International Journal of Computer Application. (NY, USA). 177(5): 25-29.
  • Atia, S. and K. Shaalan. (2015). Increasing the Accuracy of Opinion Mining in Arabic. IEEE 1st International Conference on Arabic Computational Linguistics (ACLing). (Cairo, Egypt). 106-113.
  • Fegade, P. & D. D. Patil. (2014). Mining Frequent Item sets for Improving the Effectiveness of Marketing and Sales. International Journal of Computer Science and Information Technologies. (USA). 5(3): 3736-3738.
  • Injadat, M.N., F. Salo & A. B. Nassif. (2016). Data Mining Techniques in Social Media: A Survey. Neuro computing, Elsevier. (Amsterdam, Netherlands). 214: 654-670.
  • Jadav, B. M. and V. B. Vaghela. (2016). Sentiment Analysis using Support Vector Machine based on Feature Selection and Semantic Analysis. International Journal of Computer Applications. (NY, USA). 146(13): 26-30.
  • Joshi, A., N. Pandey, R. Chawla & P. Patil. (2015). Use of Data Mining Techniques to Improve the Effectiveness of Sales and Marketing. International Journal of Computer Science and Mobile Computing. (Andhra Pradesh, India) 4(4): 81-87.
  • Kharde, V. A. & S. S. Sonawane. (2016). Sentiment Analysis of Twitter Data: A Survey of Techniques. International Journal of Computer Applications. (NY, USA). 139(11): 5-15.
  • Kumari, N. & S. Naryan Singh. (2016). Sentiment Analysis on E-commerce Application by using Opinion Mining. IEEE 6th International Conference on Cloud System and Big Data Engineering (Confluence). (Noida, India). 320-325.

Cite this article

APA

    APA : Khan, D. M., Rao, T. A., & Shahzad, F. (2019). The Classification of Customers' Sentiment using Data Mining Approaches. Global Social Sciences Review, IV(IV), 146-156. https://doi.org/10.31703/gssr.2019(IV-IV).19

CHICAGO

    CHICAGO : Khan, Dost Muhammad, Tariq Aziz Rao, and Faisal Shahzad. 2019. "The Classification of Customers' Sentiment using Data Mining Approaches." Global Social Sciences Review, IV (IV): 146-156 doi: 10.31703/gssr.2019(IV-IV).19

HARVARD

    HARVARD : KHAN, D. M., RAO, T. A. & SHAHZAD, F. 2019. The Classification of Customers' Sentiment using Data Mining Approaches. Global Social Sciences Review, IV, 146-156.

MHRA

    MHRA : Khan, Dost Muhammad, Tariq Aziz Rao, and Faisal Shahzad. 2019. "The Classification of Customers' Sentiment using Data Mining Approaches." Global Social Sciences Review, IV: 146-156

MLA

    MLA : Khan, Dost Muhammad, Tariq Aziz Rao, and Faisal Shahzad. "The Classification of Customers' Sentiment using Data Mining Approaches." Global Social Sciences Review, IV.IV (2019): 146-156 Print.

OXFORD

    OXFORD : Khan, Dost Muhammad, Rao, Tariq Aziz, and Shahzad, Faisal (2019), "The Classification of Customers' Sentiment using Data Mining Approaches", Global Social Sciences Review, IV (IV), 146-156

TURABIAN

    TURABIAN : Khan, Dost Muhammad, Tariq Aziz Rao, and Faisal Shahzad. "The Classification of Customers' Sentiment using Data Mining Approaches." Global Social Sciences Review IV, no. IV (2019): 146-156. https://doi.org/10.31703/gssr.2019(IV-IV).19