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Natural Language-Based Self-learning Feedback Analysis System

  • Pratik K. Agrawal
  • Abrar S. Alvi
  • G. R. Bamnote
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 380)

Abstract

Internet has gained a wide popularity in recent years. The people’s interaction and sharing of their views about a particular subject and providing feedback to them have increased rapidly. The feedbacks are mainly in the form of numeric rating and free text words. The numeric rating can be easily processed but to process free text words is an important task. In this paper, different approaches are reviewed and based on that a self-learning feedback analysis system is proposed, which analyzes the feedback and provides an accurate result that helps in decision making.

Keywords

Semantic Artificial intelligence Sentiment analysis Ontology 

References

  1. 1.
    Zha, Z.-J., Yu, J., Tang, J., Wang, M., Chua, T.-S.: Product aspect ranking and its applications. IEEE Trans. Knowl. Data Eng. 26(5), 136 (2014)Google Scholar
  2. 2.
    Chen, Z., Mukherjee, A., Liu, B.: Aspect extraction with automated prior knowledge learning in ACL (2014)Google Scholar
  3. 3.
    Zhu, J., Zhang, C., Ma, M.Y.: Multi-aspect rating inference with aspect-based segmentation. IEEE Trans. Affect. Comput. 3(4), 469–481 (2012)MathSciNetCrossRefGoogle Scholar
  4. 4.
    Xueke, X., Xueqi, C., Songbo, T., Yue, L., Huawei, S.: Aspect-level opinion mining of online customer reviews. In: Proceedings of the Management and Visualization of User and Network Data China Communications March (2013)Google Scholar
  5. 5.
    Zhang, X., Cui, L., Wang, Y.: CommTrust computing multi-dimensional trust by mining E-commerce feedback comments. IEEE Trans. Knowl. Data Eng. 26(7) 2014Google Scholar
  6. 6.
    Wu, D.D., Zheng, L., Olson, D.L.: A decision support approach for online stock forum sentiment analysis. IEEE Trans. Syst. Man Cybern. Syst. 44(8), 1077–1087 (2014)CrossRefGoogle Scholar
  7. 7.
    Bollegala, D., Weir, D., Carroll, J.: Cross-domain sentiment classification using sentiment sensitive thesaurus. IEEE Trans. Knowl. Data Eng. 25(8), 1719–1731 (2013)CrossRefGoogle Scholar
  8. 8.
    Liu, C.-L., Hsaio, W.-H., Lee, C.-H., Lu, G.-C. Jou, E.: Movie rating and review summarization in mobile environment. IEEE Trans. Syst. Man Cybern. Part C Appl. Rev. 42(3), 397–407 (2012)Google Scholar

Copyright information

© Springer India 2016

Authors and Affiliations

  • Pratik K. Agrawal
    • 1
  • Abrar S. Alvi
    • 1
  • G. R. Bamnote
    • 1
  1. 1.Department of Computer Science & EngineeringProf Ram Meghe Institute of Technology & ResearchBadnera AmravatiIndia

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