Feature based opinion mining for restaurant reviews

Y. R. Nithin, G. Poornalatha

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Product reviews or customer feedback has become a platform for retailers to plan marketing strategy and also for new customers to select their appropriate product. Since the trend of e-commerce is increasing, an amount of customer reviews also has been increased to a greater extent. Consequently, it becomes a tough task for retailers as well as customers to read the reviews associated with the product. Sentiment analysis resolves this issue by scanning through free text reviews and providing the opinion summary. However, it does not provide detailed information, such as features on which the product is reviewed. Feature-based sentiment analysis methods increases the granularity of sentiment analysis by analyzing polarity associated with features in the given free text. The main objective of this work is to design a system that predicts polarity at aspect level and to design a score calculating scheme that defines the extent of polarity. Obtained feature - level scores are summarized according to users’ priority of interest.

Original languageEnglish
Title of host publicationAdvances in Signal Processing and Intelligent Recognition Systems - Proceedings of 3rd International Symposium on Signal Processing and Intelligent Recognition Systems, SIRS-2017
PublisherSpringer Verlag
Pages305-318
Number of pages14
Volume678
ISBN (Print)9783319679334
DOIs
Publication statusPublished - 2018
Event3rd International Symposium on Signal Processing and Intelligent Recognition Systems, SIRS 2017 - Manipal, India
Duration: 13-09-201716-09-2017

Publication series

NameAdvances in Intelligent Systems and Computing
Volume678
ISSN (Print)2194-5357

Conference

Conference3rd International Symposium on Signal Processing and Intelligent Recognition Systems, SIRS 2017
CountryIndia
CityManipal
Period13-09-1716-09-17

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All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science(all)

Cite this

Nithin, Y. R., & Poornalatha, G. (2018). Feature based opinion mining for restaurant reviews. In Advances in Signal Processing and Intelligent Recognition Systems - Proceedings of 3rd International Symposium on Signal Processing and Intelligent Recognition Systems, SIRS-2017 (Vol. 678, pp. 305-318). (Advances in Intelligent Systems and Computing; Vol. 678). Springer Verlag. https://doi.org/10.1007/978-3-319-67934-1_27
Nithin, Y. R. ; Poornalatha, G. / Feature based opinion mining for restaurant reviews. Advances in Signal Processing and Intelligent Recognition Systems - Proceedings of 3rd International Symposium on Signal Processing and Intelligent Recognition Systems, SIRS-2017. Vol. 678 Springer Verlag, 2018. pp. 305-318 (Advances in Intelligent Systems and Computing).
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Nithin, YR & Poornalatha, G 2018, Feature based opinion mining for restaurant reviews. in Advances in Signal Processing and Intelligent Recognition Systems - Proceedings of 3rd International Symposium on Signal Processing and Intelligent Recognition Systems, SIRS-2017. vol. 678, Advances in Intelligent Systems and Computing, vol. 678, Springer Verlag, pp. 305-318, 3rd International Symposium on Signal Processing and Intelligent Recognition Systems, SIRS 2017, Manipal, India, 13-09-17. https://doi.org/10.1007/978-3-319-67934-1_27

Feature based opinion mining for restaurant reviews. / Nithin, Y. R.; Poornalatha, G.

Advances in Signal Processing and Intelligent Recognition Systems - Proceedings of 3rd International Symposium on Signal Processing and Intelligent Recognition Systems, SIRS-2017. Vol. 678 Springer Verlag, 2018. p. 305-318 (Advances in Intelligent Systems and Computing; Vol. 678).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Nithin YR, Poornalatha G. Feature based opinion mining for restaurant reviews. In Advances in Signal Processing and Intelligent Recognition Systems - Proceedings of 3rd International Symposium on Signal Processing and Intelligent Recognition Systems, SIRS-2017. Vol. 678. Springer Verlag. 2018. p. 305-318. (Advances in Intelligent Systems and Computing). https://doi.org/10.1007/978-3-319-67934-1_27