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We present an efficient genetic algorithm for mining multi-objective rules from large databases. Multi-objectives will conflict with each other, which makes it optimization problem that is very difficult to solve simultaneously. We propose a multi-objective evolutionary algorithm called improved niched Pareto genetic algorithm(INPGA), which not only(More)
A co-location pattern is a set of spatial features whose instances frequently appear in a spatial neighborhood. This paper efficiently mines the top-k probabilistic prevalent co-locations over spatially uncertain data sets and makes the following contributions: 1) the concept of the top-k probabilistic prevalent co-locations based on a possible world model(More)
Spatial co-locations represent the subsets of spatial features which are frequently located together in a geographic space. Discovering co-locations has many useful applications. For example, co-located plant species discovered from plant distribution datasets can contribute to the analysis of plant geography, phytosociology studies, and plant protection(More)
Spatial co-locations represent the subsets of spatial features which are frequently located together in a geographic space. Spatial co-location mining has been a research hot in recent years. But the research on causal rule discovery hidden in spatial co-locations has not been reported. Maybe the features in a co-location accidentally share the similar(More)
Establishing interoperability is the first and foremost problem of secure interoperation in multi-domain environments. This paper proposes a secure interoperation architecture to facilitate the establishment of secure interoperability in multidomain environments, which employ Usage Control (UCON) policies, followed with the attribute management to support(More)