Name
Abstract | ||
|---|---|---|
As more and more learners are opting for online learning, e-learning industry is working on improving learning experience of online user by providing relevant content and lot of additional references. Since online learners mostly prefer video tutorials, identifying major topics and subtopics covered in video tutorial is a big challenge. Recently, for efficient knowledge sharing and interoperability over web lot of attention is given to semantic web. In this paper, we propose a semantic web-based framework for automatic topic identification from video tutorials in order to identify the concepts and their associated semantically relevant resources. Our framework identifies relevant topic using disambiguation in e-learning resource which helps learners in more focused study. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/ISADS.2017.40 | 2017 IEEE 13th International Symposium on Autonomous Decentralized System (ISADS) |
Keywords | Field | DocType |
DBpedia,e-Learning,Natural Language Processing (NLP),ontology,Semantic web,Topic Mining,Wikipedia,WordNet | World Wide Web,Semantic Web Stack,Computer science,Interoperability,Semantic Web,Encyclopedia,Social Semantic Web,Semantics,The Internet,Electronic publishing | Conference |
ISBN | Citations | PageRank |
978-1-5090-4043-8 | 0 | 0.34 |
References | Authors | |
2 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kiran Badwaik | 1 | 0 | 0.34 |
| Khalid Mahmood Malik | 2 | 8 | 3.60 |
| Asif Raza | 3 | 5 | 1.57 |