Proposition of the recommendation system for the author based on similarity degrees

At present, there is a rapid increase of educational resources in various learning stands. The lesson producer is a fundamental as well as a responsible actor in the creation and the outline of educational resources. First, due to the cost caused by the process of producing new educational resources, and because of the fullness within these lasts. The author is invited to evade all sorts of vain duplications, and so take advantage and join the efforts. Our aim is to suggest a reference system to the author profile during the lesson creation, which may require the production of several educational resources to respond to general and specific objectives. Therefore, we have previously created a mode or a representation for the resource sought or the creation’s object by the author throughout a global ontology.In this paper, we hope for the launch of research based on the criteria drawn from the ontology and the mensuration techniques depending on the similarity degrees. We will bound this paper to two recommendations criteria that are; educational objectives and tags. Indeed, each educational resource contains, not only but an educational objective and at least a tag alone from its creation environment (Open Educational Resource, MOOC or e-learning). During the lesson creation, the author is beholden to identifying, above all the domain assigned, the specific objective, few tags and annotations or keywords; these elements are going to serve our ontology. Based the measures’ techniques of similarity amidst the author and the bank’s content of utilization cases, the recommendation system has to place a result sorted through a descending similarity degree. The author requires the possibility of updating the results by interposing under an administrator’s supervision a weighting, an indexation or a memorization related to each resource. For this reason, we firstly are going to limit our learning environment to; OER MOOC and e-learning. Then, we will limit the research domain to the Artificial Intelligence. Afterwards, we are going to perform researches on resources acknowledging the concept in question. Lastly, we will proceed to a comparative study amongst these studies in order to be able to choose the convenient technique to our work context. The first section consists of presenting the adapted method for the extraction educational resources. Thereafter, we are going to move towards the enhancement of our ontology from the identified extraction. Finally, we are going to prioritize the criteria according to our needs and present some measures techniques and choose one to adopt for our context.