Abstract
ReMashed is a Web 2.0 Mash-up environment that allows learners to personalize information of a community to their preferences. ReMashed can be used by communities to share their Web 2.0 information and further personalize the shared information to personal preferences.
ReMashed uses a recommender technology called collaborative filtering to generate recommendations. It works by matching together users with similar opinions about different resources. Each member of the system has a 'neighborhood' of other like-minded users. Ratings and Tags from these neighbors are used to create personalized recommendations. At the moment a tag and a rating based recommendation technique is applied.
The ReMashed system is written in Zend PHP, it takes advantage of the Model-View-Controller’ concept and is therefore fully object based. The recommender system builds on top of the Duine prediction engine or alternatively on self designed recommendation algorithms.
Original language | English |
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Publication status | Published - 4 Dec 2009 |
Keywords
- recommender system
- Web2.0
- informal learning
- navigation support
- duine prediction engine