Henry Dyke A. Balmeo1, Albert A. Vinluan
Information Technology Department/Graduate School, University of the East,
Manila, Philippines, College of Computer Studies, New Era University,
Quezon City, Philippines
henrydyke@yahoo.com1, aavinluan@neu.edu.ph2
Date Received: April 5, 2018; Date Revised: March 5, 2019
Asia Pacific Journal of Multidisciplinary Research
Vol. 7 No.2, 97-105
May 2019
P-ISSN 2350-7756
E-ISSN 2350-8442
CHED Recognized Journal
ASEAN Citation Index
Hanapresto: A Platform for Restaurant Businesses with Recommender System using Knowledge Extraction from Social Media and Customer Preferences 1,073 KB 3 downloads
Henry Dyke A. Balmeo1, Albert A. Vinluan Information Technology Department/Graduate...
The restaurant and mobile food performance had the highest number of company which offers nourishment benefit due to extraordinary number of consumers. With the massive number of restaurants in Manila and incredible number of customers who liked to eat out, there is issue of finding the best restaurants to eat. In association with that clients set aside plenty of opportunity to search for the restaurants that suite their preferred budget. The study expects to develop an application for small and medium enterprises (SME’s) that locates restaurants through Global Positioning System, and ranks restaurants and posts the best performing in view of social media reactions. The administrator of the system produced measurable report and positioning from extricated information from the web-based social media. The system used only using web and mobile platform. The framework essentially helped the clients and the restaurants since the application has capacities intended to satisfy both entities.
Keywords – Restaurant, Global Positioning System (GPS), Manila, Recommender System, Knowledge Extraction