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Application of Text Mining to Build a Recommendation System for Restaurants and their Dishes

by Rafey Anjum, Harsh Dev
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 155 - Number 4
Year of Publication: 2016
Authors: Rafey Anjum, Harsh Dev
10.5120/ijca2016912284

Rafey Anjum, Harsh Dev . Application of Text Mining to Build a Recommendation System for Restaurants and their Dishes. International Journal of Computer Applications. 155, 4 ( Dec 2016), 1-6. DOI=10.5120/ijca2016912284

@article{ 10.5120/ijca2016912284,
author = { Rafey Anjum, Harsh Dev },
title = { Application of Text Mining to Build a Recommendation System for Restaurants and their Dishes },
journal = { International Journal of Computer Applications },
issue_date = { Dec 2016 },
volume = { 155 },
number = { 4 },
month = { Dec },
year = { 2016 },
issn = { 0975-8887 },
pages = { 1-6 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume155/number4/26590-2016912284/ },
doi = { 10.5120/ijca2016912284 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:00:20.575767+05:30
%A Rafey Anjum
%A Harsh Dev
%T Application of Text Mining to Build a Recommendation System for Restaurants and their Dishes
%J International Journal of Computer Applications
%@ 0975-8887
%V 155
%N 4
%P 1-6
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Blogs, comments and reviews have now become an integral part of people who want to read them in order to be informed regarding other people opinion. This helps them to gain an overview of what other people say so that they might take a decision based on other people recommendation. Most of the time the user may not been in a position to read all the opinions and then take an informed decision about the product or services which he/she wants to take. Also it has been seen that most of the websites use different approach like star rating, numerical rating, to depict the information to the people who want to read the reviews. In this paper our aim is to develop a system for providing a method to help and explore good restaurants and specific dishes which a user wants to know based on past experiences of the people. The basic approach is to extract opinions from the websites and to extract the meaning of those sentences by applying Natural Language Processing techniques and then give the rating on a 5-point scale.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Natural language processing Text mining Recommendation system