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Title:
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ON EXTRACTING PERSONAL RECOMMENDATION KNOWLEDGE BASED ON THE EXPERIENCE SHARING MECHANISM OF NATURAL ANTS |
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Author(s):
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Feng-Hsu Wang , Chen-Chan Lin |
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ISBN:
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978-972-8939-17-5 |
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Editors:
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Miguel Baptista Nunes and Maggie McPherson |
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Year:
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2010 |
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Edition:
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Vol. II |
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Keywords:
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Web-based learning, personalized recommendation system, knowledge extraction, learning style |
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Type:
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Poster/Demonstration |
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First Page:
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295 |
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Last Page:
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297 |
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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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Web-based learning systems feature the multiplicity of learners and the abundance in learning resources, creating a large database tracking how users of different learning styles had learnt through the learning resources. In this research we develop a knowledge extraction model that is inspired by the experience sharing mechanism of natural ants to provide personal recommendation for web-based learning by considering learning styles, learner competency and resources characteristics. A set of preliminary simulations were conducted to investigate the behavior and effectiveness of the method in extracting personal recommendation knowledge. The results show that our approach is potentially a useful method to build real-time personal recommender for web-based learning. |
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