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International Conference on Health Information Science

HIS 2016: Health Information Science pp 129–135Cite as

A Dietary Nutrition Analysis Method Leveraging Big Data Processing and Fuzzy Clustering

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10038))

Abstract

Dietary nutrition analysis is important because it can provide scientific guidances for human to keep healthy and administrative departments to make rational decisions. However, the existing dietary nutrition analysis methods need to be improved. On the one hand, the data to be processed should be more accurate. Most methods use a sample taken at a moment time to represent all samples produced during a period of time, which neglects the fact samples may change over time. On the other hand, data analysis should be efficiently and effectively, as the number of samples is rapidly increasing and the types of samples are constantly emerging. This paper introduces a new method. Firstly, samples are preprocessed using a data model obtained by big data processing. Secondly, the fuzzy c-means algorithm is parallelized with Mapreduce for data analysis. The optimization rules are given. Finally, the experiments prove that this method is efficiently and effectively.

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References

  1. Jiang, J., et al.: Dietary intake of human essential elements from a total diet study in Shenzhen, Guangdong Province. China. J. Food Compos. Anal. 39, 1–7 (2015)

    Article  Google Scholar 

  2. Magge, H., Sprinz, P., Adams, W.G., Drainoni, M.L., Meyers, A.: Zinc protoporphyrin and iron deficiency screening: trends and therapeutic response in an urban pediatric center. JAMA Pediatr. 167(4), 361–367 (2013)

    Article  Google Scholar 

  3. Zhu, S.: Dietary surveys by microcomputer. J. Harbin Med. Univ. (3), 56–58 (1987)

    Google Scholar 

  4. Zhang, J., Liao, H.: Micro-computer applications for dietary assessment. J. Fujian Med. Coll. 20(1), 62–65 (1987)

    Google Scholar 

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Acknowledgments

This paper is supported by the National Natural Science Foundation of China (NO. 11271237) and by the Fundamental Research Funds for the Central Universities (GK201603086).

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Authors and Affiliations

  1. School of Computer Science, Shaanxi Normal University, Xi’an, 710062, China

    Lihui Lei & Yuan Cai

Authors
  1. Lihui Lei
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  2. Yuan Cai
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Corresponding author

Correspondence to Lihui Lei .

Editor information

Editors and Affiliations

  1. Victoria University , Melbourne, Australia

    Xiaoxia Yin

  2. Computer Science, New Jersey Institute of Technology, Newark, New Jersey, USA

    James Geller

  3. Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

    Ye Li

  4. Victoria University , Melbourne, Australia

    Rui Zhou

  5. Centre for Applied Informatics, Victoria University, Melbourne, Australia

    Hua Wang

  6. Centre for Applied Informatics, Victoria University, Melbourne, Australia

    Yanchun Zhang

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© 2016 Springer International Publishing AG

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Cite this paper

Lei, L., Cai, Y. (2016). A Dietary Nutrition Analysis Method Leveraging Big Data Processing and Fuzzy Clustering. In: Yin, X., Geller, J., Li, Y., Zhou, R., Wang, H., Zhang, Y. (eds) Health Information Science. HIS 2016. Lecture Notes in Computer Science(), vol 10038. Springer, Cham. https://doi.org/10.1007/978-3-319-48335-1_14

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  • DOI: https://doi.org/10.1007/978-3-319-48335-1_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-48334-4

  • Online ISBN: 978-3-319-48335-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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