SEMANTIC VIDEO ANNOTATION IN E-LEARNING FRAMEWORK Antonella Carbonaro, Rodolfo Ferrini Department of Computer Science University of Bologna Mura Anteo Zamboni 7, I-40127 Bologna, Italy Tel.: +39 0547 338830 Fax: +39 0547 338990 e_mail: carbonar@csr.unibo.it, ferrini@csr.unibo.it Abstract. The aim of this paper is twofold. In the first part we will consider the new technologies proposed as solution for the Semantic Web and then we try to outline possible applications in different fields of e-learning giving example of actual works. In the second part of the paper our proposal of improvement of an e-learning with a semantic video annotation module is presented. 1. Introduction Nowadays Web is maybe the larger available repository of resources. But when one has to look for within an enormous set of information, the research process i.e. learning material, may look as too expensive without the help of machines. The problem is that the Web was designed (and currently is) for human usage and its resources are not machine-understandable. It’s necessary adding some machine understandable meta-data to resources in order to provide and build services, agents or other kind of applications that help students in their tasks. In last years we have had an improvement in the kind of resources used as learning material. A tangible example of such trends are video resources. Automatic systems for video segmentation and annotation are the requirements of all digital video management systems. The goal is to find automatic and general procedures to segment videos into scenes and to annotate them with textual data or with metric information. Annotations could be useful for further indexing, retrieval, recommendation and so on, performed both by human users and by automated applications. The Semantic Web [Berners-Lee et al., 2001] is the proposed solution in semantic resource annotation perspective. The Semantic Web can be defined as an extension of the current Web in which meaning is added to resources so that machines are allowed to understand them better. This new architecture is based on the annotation of web documents with additional semantic data. In these last years a number of new languages have been proposed in order to carry out this task. In [Bighini and Carbonaro, 2004] is introduced the InLinx (Intelligent Links) system, a Web application that provides an on-line bookmarking service. The overall system it has been firstly improved in [Carbonaro and Ferrini, 2005], introducing concepts for classification, recommendation and document sharing to provide a better personalized semantic-based resource management. Most recently we have introduced the video annotation module Scout-v [Carbonaro et al., 2006]. Scout-V performs automatic shot detection and supports user during