Enhancing the Retrieval of Social Web-Based E-Learning Content Using Semantics Extracted from DBpedia and WordNet Ontologies
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Researchers |
Eng. Ammar ALNAHHAS - Dr. Bassel ALKHATIB - Ahmad OMAR |
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Published in |
Journal of Theoretical and Applied Information Technology, Volume 96, Number 12, June 2018 |
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Abstract |
As E-learning Tools and techniques are becoming more common and compelling, many researches have emerged lately that aims at making it more flexible and applicable. Besides, the content is getting very large nowadays, so that it is very important to develop a more accurate and robust search techniques that help users find the best learning materials that exists all along the web specially on social learning websites. In this paper we propose a new method to collect, index and retrieve learning materials, a collection algorithm is presented that can bring together content from various sources. We present a semantic indexing method that aims at weighting words of the document based on both DBpedia and Wordnet Ontologies, which proves more accurate results according to the analysis and comparison that are shown in this paper. Key words: E-learning, DBpedia, WordNet, Search Engine, Social web. |
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Link to read full paper |
