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Automated Evaluation of Restaurant Reviews

  • Unique Paper ID: 177544
  • Volume: 11
  • Issue: 12
  • PageNo: 817-822
  • Abstract:
  • Whenever we go to a new place, we always think about which place would be the best to stay, eat and explore. The main question is often "What should we eat and is this the right place to enjoy a good meal?". We are all aware of how important it is to make the right choice when it comes to food. Nutritious and high-quality food is vital in supporting overall well-being and health. Finding restaurants online can often be a challenging task. Our project simplifies this by leveraging customer feedback to provide recommendations, making it easier for users to find the best dining options. Reading all of the reviews and contrasting input with other restaurants becomes challenging and time-consuming for every person. This paper presents a simple and efficient model to predict restaurant reviews using a collection of customer feedback. Customers find it difficult to locate accurate and current information due to the dispersed nature of online evaluations and the absence of real-time analysis. Centralizing all reviews on a single platform and using machine learning to offer tailored review recommendations is one way to solve this problem, making it easier for users and improving their experience. Here, we use the NLP algorithms to analyse customer feedback and reviews.
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  • ISSN: 2349-6002
  • Volume: 11
  • Issue: 12
  • PageNo: 817-822

Automated Evaluation of Restaurant Reviews

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Impact Factor
8.01 (Year 2024)
UGC Approved
Journal no 47859

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