A text filter based multimedia content recommender for children with intellectual disability

The multimedia information has been extensively growing from a variety of sources. In order to select the useful multimedia, multimedia recommender system has been emerging as a tool to help users choose which multimedia might be interesting for them. In base this, we proposed a recommender system for aims to improve the quality of video searches, making the results obtained more appropriate to the wishes of therapists and children with disabilities. The evaluations of the videos made on the multimedia objects is carried out automatically with the help of artificial intelligence techniques, and thus allowing generating an improvement in the selection of videos related to the therapy area of language.