[go: up one dir, main page]
More Web Proxy on the site http://driver.im/ skip to main content
10.1145/3034950.3034981acmotherconferencesArticle/Chapter ViewAbstractPublication PagesicmssConference Proceedingsconference-collections
research-article

A recommendation solution for multi person dinner location

Published: 14 January 2017 Publication History

Abstract

Restaurant recommended software has been a lot, but for many people have not yet dinner, more than dinner to consider not only everyone's preferences, but also need to consider the location of dining personnel and other information. This article will introduce a solution to the multi-person dining recommendation. First of all, through the association rules mining relationship between the cuisines. Next, based on the influence of the time on the user's selection, the possible dining information is supplemented based on the result of the association rule. And then through the statistical order to be recommended for dining cuisine type. The next step is to determine the restaurant's range using the location information of the diner and the restaurant density data. The season is then used to exclude seasonally unsuitable restaurants. Finally, restaurant recommendations are based on restaurant ratings, restaurant per capita consumption, cuisine and location.

References

[1]
Li Jie. 2015. Software development and design of the wireless point meal system based on Android platform. Guangxi Normal University, 2015.
[2]
CHENG Ping-guang. 2008. Application of an improved association rule mining algorithm in a self-selected restaurant. Market Modernization, 2008, (35): 19--20.
[3]
Neumark-Sztainer, D., MacLehose, R., and Loth, K. et al. 2014. What's for dinner? Types of food served at family dinner differ across parent and family characteristics. Public Health Nutrition, 2014,17(1):145--155.
[4]
LI Jie, XU Yong, and WANG Yun-feng et al. 2009. Mining strong association rules for personalized recommendation. Systems Engineering -Theory & Practice, 2009,29 (8): 144--152.
[5]
Martin, D., Rosete, A., and Alcala-Fdez, J. et al. 2014. A New Multiobjective Evolutionary Algorithm for Mining a Reduced Set of Interesting Positive and Negative Quantitative Association Rules.IEEE transactions on evolutionary computation: A publication of the IEEE Neural Networks Council,2014,18(1):54--69.
[6]
Tutut Herawan, and Mustafa Mat Deris. 2011. A soft set approach for association rules mining. Knowledge-based systems, 2011, 24(1):186--195.
[7]
Habtemariam, B., Tharmarasa, R., and Thayaparan, T. et al. 2013. A Multiple-Detection Joint Probabilistic Data Association Filter. IEEE journal of selected topics in signal processing, 2013, 7(3):461--471.
[8]
Gregory Tauer, Rakesh Nagi, Moises Sudit et al. 2013. The Graph Association Problem: Mathematical Models and a Lagrangian Heuristic. Naval research logistics, 2013, 60(3):251--268.
[9]
Pan Yujun. 2016. Chinese cuisine. Technology Horizon, 2016, (4): 202--202.
[10]
TONG Peng. 2013. On the Role of Time Factor in Cooperative Filtering Recommendation System. China Science and Technology, 2013, (22): 26--27,29.

Recommendations

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Other conferences
ICMSS '17: Proceedings of the 2017 International Conference on Management Engineering, Software Engineering and Service Sciences
January 2017
339 pages
ISBN:9781450348348
DOI:10.1145/3034950
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

In-Cooperation

  • Wuhan Univ.: Wuhan University, China

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 14 January 2017

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. Multi person dinner
  2. association rules
  3. location information
  4. restaurant density

Qualifiers

  • Research-article
  • Research
  • Refereed limited

Conference

ICMSS '17

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • 0
    Total Citations
  • 89
    Total Downloads
  • Downloads (Last 12 months)3
  • Downloads (Last 6 weeks)0
Reflects downloads up to 03 Mar 2025

Other Metrics

Citations

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media