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Intelligent e-Restaurant using Android OS

Vinayak Ashok Bharadi, Vivek Ranjan, Nikesh Masiwal, Nikita Varma Published in Algorithm

IJAIS Proceedings on International Conference and workshop on Advanced Computing 2013
Year of Publication: 2013
© 2012 by IJAIS Journal
Series icwac Number 4
10.5120/icwac1310
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  1. Vinayak Ashok Bharadi, Vivek Ranjan, Nikesh Masiwal and Nikita Varma. Article: Intelligent e-Restaurant using Android OS. IJAIS Proceedings on International Conference and workshop on Advanced Computing 2013 ICWAC(4):18-24, July 2013. BibTeX

    @article{key:article,
    	author = "Vinayak Ashok Bharadi and Vivek Ranjan and Nikesh Masiwal and Nikita Varma",
    	title = "Article: Intelligent e-Restaurant using Android OS",
    	journal = "IJAIS Proceedings on International Conference and workshop on Advanced Computing 2013",
    	year = 2013,
    	volume = "ICWAC",
    	number = 4,
    	pages = "18-24",
    	month = "July",
    	note = "Published by Foundation of Computer Science, New York, USA"
    }
    

Abstract

The simplicity and ease of access of a menu are the main things that facilitate ordering food in a restaurant. A Tablet menu completely revolutionizes the patron's dining experience. Existing programs provide an app that restaurants can use to feed their menus into iOS & Android based tablets and make it easier for the diners to flip, swipe & tap through the menu. We here aim to provide the restaurants with a tablet menu that would recommend dishes based on a recommendation algorithm which has not been implemented elsewhere. In addition to this we run the app on an Android based tablet & not on an iOS based tablet which is more expensive alternative. We use a cloud-based server for storing the database which makes it inexpensive & secure.

Reference

  1. Tan-Hsu Tan, Ching-Su Chang, Yung-Fu Chen, Yung-Fa Huang, Tsung-Yu Liu, "Developing an Intelligent e-Restaurant With a Menu Recommender for Customer-Centric Service", Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions
  2. Tomoko Kashima, Shimpei Matsumoto, and Hiroaki Ishii, "Recommendation Method with Rough Sets in Restaurant Point of Sales System", PIMECS 2010 Vol III
  3. Ali Akhtarzada, Cristian S. Calude and John Hosking, "A Multi-Criteria Metric Algorithm for Recommender Systems", CDMTCS-400
  4. Android_Developer_Service_in http://developer. android. com/reference/android/app/Service. htht,2012
  5. Daniel Gallego Vico, Wolfgang Woerndl, Roland Bader "A Study on Proactive Delivery of Restaurant Recommendation for Android Smart phones"
  6. K. Kamarudin, "The Application of Wireless Food Ordering System", MASAUM Journal of Computing, vol. 1,pp 178-184,2009
  7. http://en. wikipedia. org: Wikipedia is a multilingual, web-based, free-content encyclopedia project operated by the Wikimedia Foundation and based on an openly editable model.
  8. Mark L. Murphy. Android Programming Tutorials, The Restaurant Store, pp93-102
  9. http://www. waitersrace. com: The International Waiters Race Community.
  10. http://www. coreservlets. com/android : Coreservlets. com provides a variety of custom Java EE, Ajax, and Android programming solutions
  11. Martinez, L. Rodriguez, R. M. , & Espinilla, M. 2009, REJA: A Geo-referenced hybrid recommender system for restaurants, Web Intelligence and Intelligent Agent Technologies, 3, 187-190.
  12. Huang, C. C. 2009, Impact Analysis of Contextual Information in a Mobile Restaurant Recommender System, Taiwan University.
  13. Tung, H. W. 2004, a Personalized Restaurant Recommender Agent for Mobile E-Service, E-Technology, E-Commerce and E-Service, 259- 262.
  14. Suchismit Mahapatra,Alwin Tareen, Ying Yang , "A Cold Start Recommendation System Using Item Correlation and User Similarity"

Keywords

Recommendation, Tablet, menu, Intelligent, Android application, restaurant