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Title:
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SELPHY: A SEMANTIC-BASED SELF-LEARNING SYSTEM |
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Author(s):
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Laercio Augusto Baldochi, Clara Moreira Senne |
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ISBN:
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978-989-8533-24-1 |
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Editors:
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Pedro Isaías and Bebo White |
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Year:
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2014 |
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Edition:
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Single |
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Keywords:
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Semantic Web, ontology, e-learning, self-learning, semantic annotation. |
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Type:
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Full Paper |
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First Page:
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155 |
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Last Page:
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162 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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Large educational content repositories are currently available due to the widespread of e-learning systems. However, exploring by oneself an educational content repository is a complex task, as these repositories usually do not present means for structuring their content. An effective way towards allowing the usage of these repositories is exploiting ontologies for semantically annotating their documents. In order to perform this task, we developed a self-learning system called SelPhy. Based on a modular architecture, the proposed system is able to perform searches in educational content repositories taking into consideration the semantic relationships between learning objects. Tests performed with real users showed that SelPhy is effective in order to support self-learning. |
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