Implicit Media Knowledge Experiments & Results
Muy-Chu Ly, Alexis Germaneau, Sio-Iong Ao · AIP conference proceedings · 2011
Implicit Media Knowledge aims to provide relevant information related to visual media without effort. It is based on the analysis of media usage from several users (e.g. a community). Algorithms based on clustering methods that extract relevant information (e.g. tags, taxonomy trees) related to a media from its usage are detailed. To validate our new approach, we propose to apply our concept and algorithms on a specific media use such as the analysis of how multiple users organize their media files. Significant results of two experiments will be highlighted. Perspectives of our work will be finally presented.