Checking The Plausibility Of Nutrient Data In Food Datasets Using Knime And Big Data

As there is no standardized food database with all products available in Europe, many developers of health apps fall back on databases of communities whose quality is often insufficient. In health apps, the quality of the data sets is critical, as poor quality lowers the user's confidence. This paper examines the plausibility of nutrient data from such data sources using similarity analysis, decision support methods and Big Data technology. During a special developed process, the plausibility of the data is to be increased. Finally, the methods used will be evaluated on the basis of test data.