Předmět Recommender Systems (PV254)

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Materiál	Typ	Datum	Počet stažení

Cíl

At the end of the course students will understand the main types of recommender systems and their application domains; be able to apply the basic recommender techniques; understand main aspects of evaluation of recommender systems and be able to analyze such evaluations. Students will also have practical experience with development of a simple recommender system or with a partial evaluation of a realistic recommender system.

Osnova

Recommender systems, motivation, applications in different domains.Types of recommender systems: non-personalized, content based, collaborative filtering, hybrid.Techniques and algorithms for recommender systems, particularly with focus on collaborative filtering (user-user, item-item, SVD).Evaluation: methodology, types of experiments, evaluation metrics, examples.Other aspects of recommender systems: explanations of recommendations, trust, attacts, ...Case studies: Amazon, Netflix, Google News, YouTube, ...Educational recommender systems, current research at Faculty of informatics.

Literatura

doporučená literaturaRecommender Systems :An Introduction. ISBN 9780521493369. infoRecommender Systems Handbook. ISBN 9780387858197. info

Požadavky

Programming skills, mathematics at the level of MB101-MB104 courses.

Garant

doc. RNDr. Aleš Horák, Ph.D.

Vyučující

doc. Mgr. Radek Pelánek, Ph.D.