Plugin of recommendation based on a hybrid method for the ranking of documents in the e-learning platforms

Authors:
Hicham Moutachaouik;Hassan Douzi;Abdelaziz Marzak;Hicham Behja;Brahim Ouhbi
Affiliations:
Laboratory IRF-SIC, Faculty of Sciences Agadir, University Ibn Zohr, Agadir, Morocco;Laboratory IRF-SIC, Faculty of Sciences Agadir, University Ibn Zohr, Agadir, Morocco;Laboratory of Information Technologies and Modeling, Faculty of Science Ben M'sik Casablanca, Casablanca, Morocco;Laboratory Command and Control of Production System, ENSAM-Meknes, Meknes, Morocco;Laboratory Command and Control of Production System, ENSAM-Meknes, Meknes, Morocco
Venue:
ICISP'12 Proceedings of the 5th international conference on Image and Signal Processing
Year:
2012

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Abstract

The objective of this work is the conception and the realization of a recommendatory system, using concepts of the web usage mining and being inspired by approaches to information filtering. This system includes a new hybrid method to rank documents web, in order to propose to the Webmaster (or admin) of platform e- learning the best available documents based of the historical to research done by learners. It is, actually a meta-search engine on the web, integrated into the e-learning platform to keep surfing traces of the learner during his searching. This will permit to have a usage basis that will be used by the system to help webmaster (admin) to make decisions about the documents to be added to the platform. The elaborated system will make it passible to propose help and assistance to learners of the platform.