To increase the relevancy of local patterns discovered from noisy relations, it makes sense to formalize error-tolerance. Our starting point is to address the limitations of state...
In frequent geographic pattern mining a large amount of patterns can be non-novel and non-interesting. This problem has been addressed recently, and background knowledge is used t...
The search for unknown frequent pattern is one of the core activities in many time series data mining processes. In this paper we present an extension of the pattern discovery pro...
The authors of topic map-based learning resources face major difficulties in constructing the underlying ontologies. In this paper we propose two approaches to address this problem...
For difficult prediction problems, practitioners often segment the data into relatively homogenous groups and then build a model for each group. This two-step procedure usually res...