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A Recommender System Based on Hierarchical Clustering for Cloud e-Learning

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Intelligent Distributed Computing XI (IDC 2017)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 737))

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Abstract

Cloud e-Learning (CeL) is a new paradigm for e-Learning, aiming towards using any possible learning object from the cloud in a smart way and generate a personalised learning path for individual learners. An issue that appears before the generation of the learning path through automated planning, is to filter a pool of resources that are relevant to the learners profile and desires in order to enhance their knowledge and skills at a higher cognitive level. In this paper, we present a Recommender System for Cloud e-Leaning (CeLRS) that uses hierarchical clustering to select the most appropriate resources and utilise a vector space model to rank these resources in order of relevance for any individual learner. We discuss the issues raised and we demonstrate how CeLRS works.

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Notes

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    ACM CCS, https://www.acm.org/publications/class-2012.

  2. 2.

    ACM CCS, https://www.acm.org/publications/class-2012.

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Correspondence to Krenare Pireva .

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Pireva, K., Kefalas, P. (2018). A Recommender System Based on Hierarchical Clustering for Cloud e-Learning. In: Ivanović, M., Bădică, C., Dix, J., Jovanović, Z., Malgeri, M., Savić, M. (eds) Intelligent Distributed Computing XI. IDC 2017. Studies in Computational Intelligence, vol 737. Springer, Cham. https://doi.org/10.1007/978-3-319-66379-1_21

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  • DOI: https://doi.org/10.1007/978-3-319-66379-1_21

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