Wireless Mobile Communication and Healthcare. 8th EAI International Conference, MobiHealth 2019, Dublin, Ireland, November 14-15, 2019, Proceedings

Research Article

Intelligent Combination of Food Composition Databases and Food Product Databases for Use in Health Applications

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  • @INPROCEEDINGS{10.1007/978-3-030-49289-2_24,
        author={Alexander Muenzberg and Janina Sauer and Andreas Hein and Norbert Roesch},
        title={Intelligent Combination of Food Composition Databases and Food Product Databases for Use in Health Applications},
        proceedings={Wireless Mobile Communication and Healthcare. 8th  EAI International Conference, MobiHealth 2019, Dublin, Ireland, November 14-15, 2019, Proceedings},
        proceedings_a={MOBIHEALTH},
        year={2020},
        month={6},
        keywords={Food data Data analysis Data mining Big Data},
        doi={10.1007/978-3-030-49289-2_24}
    }
    
  • Alexander Muenzberg
    Janina Sauer
    Andreas Hein
    Norbert Roesch
    Year: 2020
    Intelligent Combination of Food Composition Databases and Food Product Databases for Use in Health Applications
    MOBIHEALTH
    Springer
    DOI: 10.1007/978-3-030-49289-2_24
Alexander Muenzberg,*, Janina Sauer,*, Andreas Hein1,*, Norbert Roesch2,*
  • 1: Carl von Ossietzky University Oldenburg
  • 2: University of Applied Science Kaiserslautern
*Contact email: alexander.muenzberg@hs-kl.de, janina.sauer@hs-kl.de, andreas.hein@uni-oldenburg.de, norbert.roesch@hs-kl.de

Abstract

The necessity of using food data in mobile health applications is often linked with difficulties. In Europe no standardized and quality-controlled food product databases are accessible. Data from third party sources are often incomplete and have to be checked carefully before use for errors and inconsistencies. The purpose of this approach is to improve data quality and to increase information density by developing a dedicated food data warehouse. By using the extract, transform and load processes known from data warehouse technologies, multiple data sources will be combined, inserted and evaluated. The data is cleaned up by using data profiling techniques. Data mining methods are used to merge the datasets from food composition databases and food product databases to increase information density. The aim is to analyze, if and how Big Data technologies can increase performance of data processing significantly.