The impact of social similarities and event detection on ranking retrieved resources in collaborative E-learning systems

Abstract

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 net-workers. 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.