skip to main content
10.1145/3358528.3359551acmotherconferencesArticle/Chapter ViewAbstractPublication PagesicbdtConference Proceedingsconference-collections
research-article

Application of Recommender System in Intelligent Community under Big Data Scenario

Authors Info & Claims
Published:28 August 2019Publication History

ABSTRACT

Nowadays, intelligent community is one of indispensable parts in social construction. The construction of intelligent community promotes the construction and development of intelligent city, which can improve residents' living quality. Eating is an important part inhuman lives. In this paper, we develop a food recommendation system. This system is based on big data, Association Rule-based Recommendation and Collaborative Filtering Recommendation. By analyzing a large number of historical user behaviors, this system recommends restaurants, supermarkets, recipes and meal delivery service.

References

  1. Tian, C.L., Chou, Y. 2017. Research on the current situation and development trend of smart community. China New Telecommunications. 18,57.Google ScholarGoogle Scholar
  2. Chen, L, Lu, Q, Qiao, J.J. 2016. Research on the Construction of the Wisdom Community Endowment Service System. Population Journal, 38,3, 67--73.Google ScholarGoogle Scholar
  3. Hu, D., Bai, R.D. 2018. The Latest Practice of Smart Community Policy in Taiwan. Shanghai Urban Planning Review. 01, 20-26.Google ScholarGoogle Scholar
  4. Chen,C.J,Wang,S.L. 2018. Discussion on the construction of smart community in shenzhen. Management Observer. 06, 106--107.Google ScholarGoogle Scholar
  5. Chou,Y. 2018. Research on intelligent application status and solutions of smart community. Digital communication world.01, 128+222.Google ScholarGoogle Scholar
  6. Yang, X, Yang, Y. D. 2016. Preliminary of Internet+Intelligent Food Markets:Double platform renovation of Guangzhou xigang food market. Design Community, 3, 141--150.Google ScholarGoogle Scholar
  7. Keller, R.B., Keller, B. J., Mirza, B. J.,Grama, A.Y., Karypis, G. 2001. Privacy risks in recommender systems. IEEE Internet Computing, 5,6, 54--62.Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Deng, S. G., Huang, L. T., Wu, J., Wu, Z. H. 2014. Trust-based personalized service recommendation: a network perspective. Journal of Computer Science and Technology, 29, 1, 69--80.Google ScholarGoogle ScholarCross RefCross Ref
  9. Hu, J., Wang, B., Liu, Y., Li, D. Y.2012. Personalized tag recommendation using social influence. Journal of Computer Science and Technology, 27, 3, 527--540.Google ScholarGoogle ScholarCross RefCross Ref
  10. Sugiyama, K., Kan, Min-Yen.2010.Scholarly paper recommendation via user's recent research interests. Joint Conference on Digital Libraries. ACM, 29--38Google ScholarGoogle Scholar
  11. Yu, P.C. 2016. User session recommendations based on deep neural networks(Doctoral dissertation). Zhejiang University.Google ScholarGoogle Scholar
  12. Shao, F. S. 2018. Personalized book recommendation based on collaborative filtering and association rules(Doctoral dissertation). Zhejiang Gongshang University.Google ScholarGoogle Scholar
  13. Yang, H. 2013. Improved collaborative filtering recommendation algorithm based on weighted association rules. Applied Mechanics and Materials, 411--414, 94--97.Google ScholarGoogle Scholar
  14. Chen, Q. W. 2017. Research on recommendation system based on association rules and neural network analysis. Hangzhou Dianzi University.Google ScholarGoogle Scholar

Index Terms

  1. Application of Recommender System in Intelligent Community under Big Data Scenario

    Recommendations

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in
    • Published in

      cover image ACM Other conferences
      ICBDT '19: Proceedings of the 2nd International Conference on Big Data Technologies
      August 2019
      382 pages
      ISBN:9781450371926
      DOI:10.1145/3358528

      Copyright © 2019 ACM

      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]

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 28 August 2019

      Permissions

      Request permissions about this article.

      Request Permissions

      Check for updates

      Qualifiers

      • research-article
      • Research
      • Refereed limited

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader