Food Dishes Recommendation System Based on Mobile Context-Aware Services

Authors

  • Imran Shaikh  Computer Engineering Department, AAEMF’S COE & MS, Koregaonbhima, Pune, Maharashtra, India
  • Manitha Samarsen  Computer Engineering Department, AAEMF’S COE & MS, Koregaonbhima, Pune, Maharashtra, India
  • Punita Vyas  Computer Engineering Department, AAEMF’S COE & MS, Koregaonbhima, Pune, Maharashtra, India

Keywords:

Android, Big Data, HDFS, Hadoop, Mapreduce, Smart Phones.

Abstract

Context information, such as user location, age, and user profile, Gender, Comments has been popularly applied to analyze user behaviour. In this paper, we develop a Food Dishes recommendation system based on mobile context aware services to provide customized information for users. We analyze the service satisfaction ratings of the users to recommend favored Food Dishes for them. With mobile context awareness, the proposed framework can substantially enhance the capacity to satisfy the user demands for Food Dishes recommendations.

References

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  3. VarshaChavan, PriyaJadhav, SnehalKorade and PriyankaTeli. "Implementing Customizable Online Food Ordering System Using Web Based Application", IJISET - International Journal of Innovative Science, Engineering & Technology, Vol. 2 Issue 4, April 2015.
  4. FAN YANG, ZHI-MEI WANG. "An Optimized Mobile Restaurant Recommend System", Proceedings of the 10th WSEAS International Conference on AUTOMATION & INFORMATION, 2009.
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International Journal of Scientific Research in Science, Engineering and Technology

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Published

2016-06-30

Issue

Volume 2, Issue 3, May-June-2016

Section

Research Articles

License

Copyright (c) IJSRSET

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Imran Shaikh, Manitha Samarsen, Punita Vyas "Food Dishes Recommendation System Based on Mobile Context-Aware Services" International Journal of Scientific Research in Science, Engineering and Technology (IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 2, Issue 3, pp.465-468, May-June-2016.