This paper addresses the challenging problem of learning from multiple annotators whose labeling accuracy (reliability) differs and varies over time. We propose a framework based ...
Adaptable similarity queries based on quadratic form distance functions are widely popular in data mining applications, particularly for domains such as multimedia, CAD, molecular ...
Adaptable similarity queries based on quadratic form distance functions are widely popular in data mining application domains including multimedia, CAD, molecular biology or medica...
Learning from data streams is a research area of increasing importance. Nowadays, several stream learning algorithms have been developed. Most of them learn decision models that c...
Nowadays, graph-based knowledge discovery algorithms do not consider numeric attributes (they are discarded in the preprocessing step, or they are treated as alphanumeric values w...
Oscar E. Romero, Jesus A. Gonzalez, Lawrence B. Ho...