Using Data Mining in a Recommender System to Search for Learning Objects in Repositories.
Alfredo Zapata González, Víctor Hugo Menéndez Domínguez, Manuel E. Prieto, Cristóbal Romero · Educational Data Mining · 2011
Firstly, a user does a query using the search engine based on keywords and/or values of some relevant metadata associated with LOs in order to preselect only a subset of LOs that contain the desired contents. Then four filtering or recommendation techniques are applied in parallel: filter by usage (with a ranking of the most commonly downloaded LOs), filter by evaluation (to rank according to the best LOs evaluated), filter by content similarity (ranked according to the most similar LOs) and filter by profile similarity (according to the most similar users/authors). The last two filters use the Nearest Neighbors approach (Ricci et al., 2011) that is like a lazy leaner classification algorithm. For a given LO or user, it compares the LO’s or user’s attributes to the rest of the LO __________________________________________________________________________________________