A Location Analytics Algorithm to Analyze Geographic and Demographic Data for Restaurant Analytics
This paper presents a location analytics algorithm that takes this influential demographic information into account and analyzes the spots-in combination with geographical data-to recommend locations based on these two factors.
Abstract
Nowadays, big data are everywhere. These include geographic and/or demographic data. Location usually plays a critical role in determining a restaurant's success, especially in today's society. Selecting an appropriate place will not only help entrepreneurs attract more customers but also maintain the stability of their businesses. Hence, location analysis has always been a focused topic. However, if entrepreneurs consider solely the direct aspects of the location (e.g., rental price, competitors), it will not likely be sufficient as customer-related aspects (e.g., income level, age) also greatly affect the compatibility of the establishment. In this paper, we present a location analytics algorithm that takes this influential demographic information into account and analyzes the spots-in combination with geographical data-to recommend locations based on these two factors. Evaluation results on real-world data from the USA shows the practicality of our solution.