Massimo Quadrana

Massimo Quadrana
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Massimo Quadrana
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Computer Science - Information Retrieval (2)
 
Computer Science - Multimedia (1)
 
Computer Science - Computer Vision and Pattern Recognition (1)

Publications Authored By Massimo Quadrana

Item features play an important role in movie recommender systems, where recommendations can be generated by using explicit or implicit preferences of users on traditional features (attributes) such as tag, genre, and cast. Typically, movie features are human-generated, either editorially (e.g. Read More

One of the main challenges in Recommender Systems (RSs) is the New User problem which happens when the system has to generate personalised recommendations for a new user whom the system has no information about. Active Learning tries to solve this problem by acquiring user preference data with the maximum quality, and with the minimum acquisition cost. Although there are variety of works in active learning for RSs research area, almost all of them have focused only on the single-domain recommendation scenario. Read More