Collaborative filtering is a popular approach for building recommender systems. Current collaborative filtering algorithms are accurate but also computationally expensive, and so ...
Based on the type of collaborative objects, a collaborative filtering (CF) system falls into one of two categories: item-based CF and user-based CF. Clustering is the basic idea i...
Selective sampling, a form of active learning, reduces the cost of labeling training data by asking only for the labels of the most informative unlabeled examples. We introduce a ...
Background: When term ambiguity and variability are very high, dictionary-based Named Entity Recognition (NER) is not an ideal solution even though large-scale terminological reso...
Yutaka Sasaki, Yoshimasa Tsuruoka, John McNaught, ...
Although significant progress has been made toward effective insight discovery in visual sense making approaches, there is a lack of effective and efficient approaches to manage t...