The Impact of Social Similarities and Event Detection on Ranking Retrieved Resources in Collaborative E-Learning Systems

Recently, the social web has recognized a real attention by E-learning community. This collaborative space gave students new opportunities to share their contents and receive immediate feedback from other networkers. For instance, in folksonomies, learners are able to tag useful resources within a highly visible space, which allow sharing ideas that gives a basis for discussion, and thus other students can benefit from those resources. Actually, social environments offer a unique opportunity to personalize search spaces. The objective of this work is to achieve this opportunity and thus personalize tag-based search in E-learning folksonomy by extract implicitly the semantics of learners’ tags. In this context, a social personalized ranking function is proposed; this function leverages the social aspect of folksonomy and events detection to estimate the relevance of given resources to a tag-based query issued by learners.