An intelligent e-learning scenario for knowledge retrieval

E-Learning is a critical support mechanism for educational institutions to grow the performance of their students, teachers, as well as useful for organizations to enhance the performance of their employees. The efficient retrieval of learning knowledge is a critical support mechanism for educational institutions to enhance the skills of their students and at the same time useful for learning process. Teachers and students face many difficulties when working with knowledge retrieval in education. Studies show that still it demands more effective approach. Semantic and Artificial Intelligence represent potential technologies for realizing e-Learning requirements. The convergence of e-Learning and digital libraries creates challenge to be solved not only at storage resources level but also at the knowledge retrieval level. Nowadays availability of infrastructure, flexibility of time, learning resources and their means of sharing has increased adaptability of Digital Library to learn and attain knowledge to a great extent. The objective of our study is to present an e-learning management system for Digital Library in Seville University that provides a general platform for learning environment. The idea is investigated from a search perspective possible intelligent infrastructures form constructing decentralized digital libraries where a global semantic schema exists. We suggest a conceptual architecture for a semantic and intelligent search engine. This project is a collaborative effort that proposes a new form of interaction between engineering students and E-learning platform, where the latter is adapted to individuals and their surroundings. We propose a comprehensive approach for discovering information objects in large digital collections based on analysis of recorded semantic metadata and the application of Artificial Intelligent technologies.