Data sparsity, scalability and prediction quality have been recognized as the three most crucial challenges that every collaborative filtering algorithm or recommender system conf...
Kernel conditional random fields (KCRFs) are introduced as a framework for discriminative modeling of graph-structured data. A representer theorem for conditional graphical models...
Abstract. Similarity computation is a difficult issue in music information retrieval, because it tries to emulate the special ability that humans show for pattern recognition in ge...
Medical assessment of penetrating injuries is a difficult and knowledge-intensive task. Physical examination and computed tomographic (CT) imaging data must be combined with detai...
Daniel L. Rubin, Olivier Dameron, Yasser Bashir, D...
Satisfaction surveys are an important measurement tool in fields such as market research or human resources management. Serious studies consist of numerous questions and contain a...