image-based dietary information mining for community creation in a social network
We present the initial results of an investigation on automated community formation in a social networking site, named FoodLog , that manages dietary information of its users. The site analyzes photos submitted by users, to estimate the dietary composition of their daily meals. In order to automatically identify natural groupings among meals consumed by different users, we apply simple expectation maximization algorithm on a selected data set from this site. Visual observation of images from the resulting clusters proves that the groupings actually correspond to different categories of meals. We demonstrate how communities of users can be formed by assigning them to clusters. We also discuss the steps that should follow this initial study, and possible future directions.
foodlog clustering dietary data mining multimedia