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Analysis on Increasing Customer Sales by the Use of Restaurant Recommender System

by M. Ashrafa, M. Lalitha, D. Radha, R. Jayaparvathy
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 139 - Number 7
Year of Publication: 2016
Authors: M. Ashrafa, M. Lalitha, D. Radha, R. Jayaparvathy
10.5120/ijca2016909178

M. Ashrafa, M. Lalitha, D. Radha, R. Jayaparvathy . Analysis on Increasing Customer Sales by the Use of Restaurant Recommender System. International Journal of Computer Applications. 139, 7 ( April 2016), 9-10. DOI=10.5120/ijca2016909178

@article{ 10.5120/ijca2016909178,
author = { M. Ashrafa, M. Lalitha, D. Radha, R. Jayaparvathy },
title = { Analysis on Increasing Customer Sales by the Use of Restaurant Recommender System },
journal = { International Journal of Computer Applications },
issue_date = { April 2016 },
volume = { 139 },
number = { 7 },
month = { April },
year = { 2016 },
issn = { 0975-8887 },
pages = { 9-10 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume139/number7/24500-2016909178/ },
doi = { 10.5120/ijca2016909178 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:40:17.547801+05:30
%A M. Ashrafa
%A M. Lalitha
%A D. Radha
%A R. Jayaparvathy
%T Analysis on Increasing Customer Sales by the Use of Restaurant Recommender System
%J International Journal of Computer Applications
%@ 0975-8887
%V 139
%N 7
%P 9-10
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In a restaurant recommender system the main focus is on the user rating or perhaps the customer satisfaction that is significant of all. The contextual features are closely studied which aids as the precipitate for the study. In order to identify relevant contextual information for the study, only those cardinal features that are significant for the decision criteria are considered. Subsequently these features which are identified are used for the analysis. However, insignificant features may not scale up well for the study. This reduces dimensionality issues. Previously this kind of an approach using contextual feature has been utilized for various studies in restaurant recommender system. This is of prime importance in order to build the relevant contextual user profile. The customer rating or the level of satisfaction stated by the customer is used to study the perception of the restaurant by the customer. Also to extract those customers who visit a particular restaurant moderately than in comparison with those who visits very often or visits less than moderate. These customers are extracted to be focused upon for increase of sale by sending them text messages or emails regarding the offers and other discounts which is more economical rather than sending those offers to every customer visiting the restaurant.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Contextual information feature selection.