— We introduce a graph-based relational learning approach using graph-rewriting rules for temporal and structural analysis of biological networks changing over time. The analysis...
We consider the problem of characterisation of sequences of heterogeneous symbolic data that arise from a common underlying temporal pattern. The data, which are subject to impreci...
Mining massive temporal data streams for significant trends, emerging buzz, and unusually high or low activity is an important problem with several commercial applications. In th...
Sensor networks have increased the amount and variety of temporal data available, requiring the definition of new techniques for data mining. Related research typically addresses...
Leonardo E. Mariote, Claudia Bauzer Medeiros, Rica...
Abstract. We propose a learning approach for integrating formal knowledge into statistical inference by exploiting ontologies as a semantically rich and fully formal representation...