EZServd : recommender system for food service

Abstract

The service in food serving establishments has a lot of room for improvement. Lack of proper communication causes the dining experience for both the businesses and their clients to deteriorate. Currently, the interaction methods are outdated and error prone. Once the customer knows what they would like to have, placing the order requires them to grab the attention of the right waitstaff, verbally relay the information of what every single person sitting at that table would like to eat and drink, and hope that the waitstaff successfully takes and passes on the order to the kitchen. In addition to these common problems, another set of complications present themselves for countries with higher number of international residents. The language barrier creates discord between customers and establishment and limits the interaction to a great degree. EZServd is our solution to these problems. It is an in-house ordering assistant that allows the customers to place and track their orders digitally using their own devices in their own language. It is a platform that carries the communication to digital realm, bypassing the once mandatory physical interaction with the waitstaff. Besides providing ease during order placement, EZServd also helps the customer with their decision-making process to enhance the dining experience. With its embedded recommender system, EZServd can offer suggestions to its users based on four different criteria called suggestion modules. These are Demographics, Finance, Speed and Chef’s Recommendation. Each module stimulates how a potential customer decides on what to order in a food serving establishment to cater to a greater number of customers.

Date of Award	2017
Original language	English
Awarding Institution	The Hong Kong University of Science and Technology