Authors :
L. Satya Naga Veni; M. Jahnavi Padmapriya; P. Srinu Vasarao
Volume/Issue :
Volume 9 - 2024, Issue 3 - March
Google Scholar :
https://tinyurl.com/3bs665n8
Scribd :
https://tinyurl.com/3xvw4afu
DOI :
https://doi.org/10.38124/ijisrt/IJISRT24MAR668
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Abstract :
Wherever we go we will definitely look for food
without any time limit. The food is an all-time emotion for
everyone. Mainly if anyone visits the new place, he/she is
excited to look for good food within less budget, with good
management, maintenance and neatness.
Zomato is a digital platform that serves as a one-stop
destination is ordering food from various restaurants. It
users with an extensive data set of restaurants, menus,
user reviews, and ratings, allowing them to browse.
Zomato is such an interesting app which provides users
with more comforts like how many users are approaching
to the Zomato, ratings, reviews, restaurants data sets, fast
hand delivery, to easily track the order by push up
notifications or delivery boy phone number. Mainly
Zomato has many facilities whatever food we need we can
easily order within seconds. The Zomato has many
different food items in different locations within the
city/town but some times the restaurants are closed early.
Mostly everyone looks for the best biriyanis within their
area because the biriyani is not a food but its an heartful
emotion who really look for it.
Can use supervised machine learning algorithms as
logistic regression, naive Bayes or support vector
machines, classify the reviews as fake or genuine based on
this feature. Every order served by the delivery boy has
the charge for delivery. In the present modernized world,
fame of food applications is expanding because of
usefulness, view, book or request effectively by not very
many snaps on telephone. Online reviews have become
very easy to take users insight to get the good
food in this app. has made it is solid and is currently
present in 22countries with more than 1,000,000 eateries
around the world and gets 1.25 million orders day to day.
Keywords :
Fake Review, Linear Regression, Logistic Regression, Naive Bayes, Machine Learning Algorithm.
Wherever we go we will definitely look for food
without any time limit. The food is an all-time emotion for
everyone. Mainly if anyone visits the new place, he/she is
excited to look for good food within less budget, with good
management, maintenance and neatness.
Zomato is a digital platform that serves as a one-stop
destination is ordering food from various restaurants. It
users with an extensive data set of restaurants, menus,
user reviews, and ratings, allowing them to browse.
Zomato is such an interesting app which provides users
with more comforts like how many users are approaching
to the Zomato, ratings, reviews, restaurants data sets, fast
hand delivery, to easily track the order by push up
notifications or delivery boy phone number. Mainly
Zomato has many facilities whatever food we need we can
easily order within seconds. The Zomato has many
different food items in different locations within the
city/town but some times the restaurants are closed early.
Mostly everyone looks for the best biriyanis within their
area because the biriyani is not a food but its an heartful
emotion who really look for it.
Can use supervised machine learning algorithms as
logistic regression, naive Bayes or support vector
machines, classify the reviews as fake or genuine based on
this feature. Every order served by the delivery boy has
the charge for delivery. In the present modernized world,
fame of food applications is expanding because of
usefulness, view, book or request effectively by not very
many snaps on telephone. Online reviews have become
very easy to take users insight to get the good
food in this app. has made it is solid and is currently
present in 22countries with more than 1,000,000 eateries
around the world and gets 1.25 million orders day to day.
Keywords :
Fake Review, Linear Regression, Logistic Regression, Naive Bayes, Machine Learning Algorithm.
