Mining sequential patterns aims at discovering correlations between events through time.
However, even if many works have dealt with sequential pattern mining, none of them …

In this paper we propose a lattice-based approach intended for extracting semantics from
datacubes: borders of version spaces for supervised classification, closed cube lattice to …

Datacubes are especially useful for answering efficiently queries on data warehouses.
Nevertheless the amount of generated aggregated data is huge with respect to the initial …

In various approaches, data cubes are pre-computed in order to efficiently answer Olap
queries. Such cubes are also successfully used for multidimensional analysis of data …

In this paper we propose a lattice-based approach intended for summarizing the Data
Cubes. With this intention, we introduce a novel concept: the cube closure over the cube …

Data cubes capture general trends aggregated from multidimensional data from a
categorical relation. When provided with two relations, interesting knowledge can be …

Discovering trend reversals between two data cubes provides users with a novel and
interesting knowledge when the real world context fluctuates: What is new? Which trends …

In this paper we use the novel concept of minimal cube transversals on the cube lattice of a
categorical database relation for mining the borders of the difference of two datacubes. The …

Real-world phenomena have traditionally been modelled in 2D/3D GIS. However, powerful
insights can be gained by integrating additional non-spatial dimensions, such as time and …

In various approaches, data cubes are pre-computed in order to efficiently answer Olap
queries. Such cubes are also successfully used for multidimensional analysis of data …