Catching the recent trend of data is an important issue when mining frequent itemsets from data streams. To prevent from storing the whole transaction data within the sliding windo...
We present a framework for mining frequent trajectories, which are translated and/or rotated with respect to one another. We then discuss a multiresolution methodology, based on th...
Alexander Andreopoulos, Bill Andreopoulos, Aijun A...
Privacy-preserving data mining techniques could encourage health data custodians to provide accurate information for mining by ensuring that the data mining procedures and results ...
A mobile node in ad hoc networks may move arbitrarily and acts as a router and a host simultaneously. Such a characteristic makes nodes in MANET vulnerable to potential attacks. Th...
While null space based linear discriminant analysis (NLDA) obtains a good discriminant performance, the ability easily suffers from an implicit assumption of Gaussian model with sa...
This work presents a kernel method for clustering the nodes of a weighted, undirected, graph. The algorithm is based on a two-step procedure. First, the sigmoid commute-time kernel...
Abstract. In our previous studies, Genetic Programming (GP), Probabilistic Incremental Program Evolution (PIPE) and Ant Programming (AP) have been used to optimal design of Flexibl...
Abstract. Contrast set mining aims at finding differences between different groups. This paper shows that a contrast set mining task can be transformed to a subgroup discovery ta...
Petra Kralj, Nada Lavrac, Dragan Gamberger, Antoni...
In this study, we propose a novel evolutionary algorithm-based clustering method, named density-sensitive evolutionary clustering (DSEC). In DSEC, each individual is a sequence of ...