A semantic enabled intelligent search system for educational information resources

Abstract

Aiming at the special requirements oriented to the education field, this paper proposes an intelligent search system based on semantic web. Under the guidance of the users' needs and the proposed Education Information Intelligent Search (EIIS) framework, the EIISReasoning mechanism and its relevant rule sets are constructed to automatically reason the search concepts in order to self-adapt semantics to more levels, where the semantic factor SR and the response time factor TR are both introduced to detail field application requirements. After this, the EIISRanking algorithm applies two levels ranking by the weight factor of semantic similarity, and the same relevance is differentiated in terms of education field needs. The case test shows that the semantic based intelligent search system takes on a better precision rate, and the ranking algorithm can improve execution performance.

Adding and Segmenting Educational Videos: Experiences of Teacher Users in an Educational Portal

“…In the literature we can find studies setting forth architectures of educational semantic portals such as [22], which presents the university semantic portal UNI-POINT; [23], which characterizes the Portal Esperonto implemented in the scope of a project of the Polytechnic University of Madrid; [24], which refers to the REASE portal, belonging to the European Association for Semantic Web Education -EASE for Education in the Semantic Web and [25], which brings about the educational semantic portal POSEDU. Other works, although not clarifying that they are about portals, refer to architectures of web systems that use semantics, such as that presented in [26], of a system of collaborative annotation of multimedia contents to be used in schools, however, it is not stated on its implementation, in [27], the Educational Information Intelligent Search -EIIS, which provides intelligent search for educational resources and in [28], the MSSearch system integrated with the Linnaeus system for storing learning objects. Table 1 shows comparative analysis of some features of each one of those semantic portals and systems.…”

“…In [24] the system has been architected so that the contents are collected and annotated with appropriate metadata by the administrator him/herself. In the portal and the system presented in [25] and [27], respectively, there are mechanisms that automatically add metadata from web content. In the system in [28], the addition of metadata can be performed in collaborative action of the users with the help of a metadata semi-automatic filling mechanism.…”

“…Another aspect analyzed in these portals and systems was concerned to the type of educational content they store. In the portals presented in [22] and [25] the contents are general educational, as it is in the system that appears in [27]; the portal presented in [23] contains specifically research projects; in [24], the portal stores contents of semantic web teaching; in [26], the proposed system architecture will allow the management of multimedia content to be used in schools; and in [28], the system stores learning objects, especially for examples involving videos.…”