research-article

Feature-based Restaurant Customer Reviews Process Model using Data Mining

Authors:

Anish Kumar Varudharajulu,

Yongsheng MaAuthors Info & Claims

ICCBD '18: Proceedings of the 2018 International Conference on Computing and Big Data

Pages 32 - 37

https://doi.org/10.1145/3277104.3277113

Published: 08 September 2018 Publication History

Abstract

Mining social media is a popular strategy to revitalize any business. The social media lodges colossal amount of user spawn data which can be used for data mining. The purpose of this research paper is to develop a feature-based software model to analyze customer reviews of an organization using their Facebook page and provide valuable insights for decision making, product quality development, and process improvements. Thus enabling concurrent engineering activities and enhancing collaboration between various departments within the organization. As a sample case study, we have analyzed the customer reviews of a restaurant using the J48 classification algorithm and K-means clustering algorithm to identify areas which need improvement. Results show that customers are giving more importance to features such as the taste, variety of drinks, price, and service, In addition, customers are least bothered about the location, offers, and ambiance of the South Indian restaurant under study.

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Cited By

Aktas E(2024)Big Data Applications in Supply Chain ManagementThe Palgrave Handbook of Supply Chain Management10.1007/978-3-031-19884-7_74(1301-1325)Online publication date: 2-Feb-2024
https://doi.org/10.1007/978-3-031-19884-7_74
Aktas E(2022)Big Data Applications in Supply Chain ManagementThe Palgrave Handbook of Supply Chain Management10.1007/978-3-030-89822-9_74-1(1-25)Online publication date: 27-Jul-2022
https://doi.org/10.1007/978-3-030-89822-9_74-1
Davis STabrizi N(2021)Customer Review Analysis: A Systematic Review2021 IEEE/ACIS 6th International Conference on Big Data, Cloud Computing, and Data Science (BCD)10.1109/BCD51206.2021.9581965(91-97)Online publication date: 13-Sep-2021
https://doi.org/10.1109/BCD51206.2021.9581965

Index Terms

Feature-based Restaurant Customer Reviews Process Model using Data Mining
1. Information systems
  1. Information systems applications
    1. Data mining
      1. Clustering

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cover image ACM Other conferences

ICCBD '18: Proceedings of the 2018 International Conference on Computing and Big Data

September 2018

103 pages

ISBN:9781450365406

DOI:10.1145/3277104

Copyright © 2018 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Publication History

Published: 08 September 2018

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ICCBD '18

ICCBD '18: 2018 International Conference on Computing and Big Data

September 8 - 10, 2018

SC, Charleston, USA

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Cited By

Aktas E(2024)Big Data Applications in Supply Chain ManagementThe Palgrave Handbook of Supply Chain Management10.1007/978-3-031-19884-7_74(1301-1325)Online publication date: 2-Feb-2024
https://doi.org/10.1007/978-3-031-19884-7_74
Aktas E(2022)Big Data Applications in Supply Chain ManagementThe Palgrave Handbook of Supply Chain Management10.1007/978-3-030-89822-9_74-1(1-25)Online publication date: 27-Jul-2022
https://doi.org/10.1007/978-3-030-89822-9_74-1
Davis STabrizi N(2021)Customer Review Analysis: A Systematic Review2021 IEEE/ACIS 6th International Conference on Big Data, Cloud Computing, and Data Science (BCD)10.1109/BCD51206.2021.9581965(91-97)Online publication date: 13-Sep-2021
https://doi.org/10.1109/BCD51206.2021.9581965

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