A common problem in food science concerns the assessment of the quality of food samples. Typically, a group of panellists is trained exhaustively on how to identify different quality indicators in order to provide absolute information, in the form of scores, for each given food sample. Unfortunately, this training is expensive and time-consuming. For this very reason, it is quite common to search for additional information provided by untrained panellists. However, untrained panellists usually provide relative information, in the form of rankings, for the food samples. In this paper, we discuss how both scores and rankings can be combined in order to improve the quality of the assessment.
CITATION STYLE
Sader, M., Pérez-Fernández, R., & De Baets, B. (2018). Combining absolute and relative information in studies on food quality. In Communications in Computer and Information Science (Vol. 854, pp. 379–388). Springer Verlag. https://doi.org/10.1007/978-3-319-91476-3_32
Mendeley helps you to discover research relevant for your work.