A Customer Service Chatbot for E-commerce Websites

A Customer Service Chatbot for E-commerce Websites

1 Mrs. S.Sarjun Beevi , 2 Aatif Aalam, 3Abhishek Anand, 4Abhishek Kumar , 5Tale Atharva Sureshrao

 1 Assistant professor, School of Computing, Department of Computer Science and Engineering, Bharath Institute of Higher Education and Research, Chennai, India- 600073.

2,3,4,5 Student, School of Computing, Department of Computer Science and Engineering, Bharath Institute of Higher Education and Research, Chennai, India- 600073.

1 sarjunbeevi.cse@bharathuniv.ac.in , 2 alamatif615@gmail.com , 3 abhishekraja0410@gmail.com , 4 abhi2000.mishra10@gmail.com , 5 atharvtale2002@gmail.com

Abstract: Basically, we are developing restaurant recommendation mobile application for both android and iOS Consumers are depending more and more on reviews from other users to help them choose what to buy, what to watch in movies, what to read, and where to eat. These questions are typically addressed by peers through referrals (word of mouth, blog entries and evaluations) or professional guidance (columnist, librarian). These days, there are many platforms for crowdsourced business reviews. Applications like Yelp, TripAdvisor, and Google offer a wealth of information about nearby companies, particularly eateries. Due to the seemingly endless options available for food and services, users frequently struggle to make decisions that meet their unique needs and wants, which adds to information overload. Accurate and customized recommendations from a recommender system are one way to solve the issue. This will significantly cut down on the time and effort required to discover new restaurants.

Keywords: Restaurant Recommendation, collaboration, filtering,