Header menu link for other important links
Developing an improvised E-menu recommendation system for customer
, Shashikant Ghumbre, Ratnadeep Deshmukh
Published in Springer Nature Singapore
Volume: 708
Pages: 333 - 343
Various operations performed by waiters like starting from taking orders till delivery of food/menu to the customer, also billing by cashier made manually. Due to manual process and paperwork may cause time delay, ignorance of customer, errors in billing leads to dissatisfaction of customers. As in today's digital era, customers expect high quality, smart services from restaurant. So to improve quality of service and to achieve customer satisfaction, we proposed improvised E-Menu Recommendation System. This system can build e-reputation of restaurant and customer community in live. All orders and expenses are stored in database and give statistics for expenses and profit. The proposed recommender system uses wireless technology and menu recommender to build improvised E-Menu Recommendation System for customer-centric service. Professional feels and environment are provided to the customers/delegates with additional information about food/menu by using interactive graphics. Outcomes of experimental are obtained by comparing results of two data mining algorithms Apriori and FP-growth which have practical potential in providing customer-centric service.
About the journal
JournalData powered by TypesetAdvances in Intelligent Systems and Computing
PublisherData powered by TypesetSpringer Nature Singapore
Open AccessNo