Automatic Summarization on Restaurants Opinion Mining

Authors

  • Miss Sonal Anil Rathi  Department of Computer Science & Engineering, P. R. Pote (Patil) College of Engineering & Management, Amravati, Maharashtra, India
  • Prof. Krutika K Chhajed  Department of Computer Science & Engineering, P. R. Pote (Patil) College of Engineering & Management, Amravati, Maharashtra, India

DOI:

https://doi.org/10.32628/IJSRST218414

Keywords:

Automatic opinion summarization, restaurant reviews and rank, nearby restaurants lookup application-KNN, sentiment analysis, multi-keyword ranked search.

Abstract

Innovation has been a fundamental piece of our lives. When going bent another cafe/restaurants or bistro, individuals normally use sites or applications to question close by spots and afterward select one hooked in to normal rating. Notwithstanding, the traditional rating is now and again insufficient to foresee the character of the café as individuals have alternate points of view and wishes while assessing an eatery. During this paper, an overview framework for sentiments in eatery audits is proposed. The framework may be a useful device for clients during a hurry to assist them improve decisions about the nature of a restaurant while saving their time. This is often finished via naturally and rapidly furnishing the clients with a synopsis of the sentiments within the café's/restaurants surveys. The proposed synopsis framework has been actualized during a versatile area based application with KNN Algorithm and Multi keyword search it accomplished a high convenience score.

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International Journal of Scientific Research in Science and Technology

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Published

2021-08-30

Issue

Volume 8, Issue 4, July-August-2021

Section

Research Articles

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How to Cite

[1]
Miss Sonal Anil Rathi, Prof. Krutika K Chhajed "Automatic Summarization on Restaurants Opinion Mining" International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011,Volume 8, Issue 4, pp.30-35, July-August-2021. Available at doi : https://doi.org/10.32628/IJSRST218414