Automatic recovery of 3D human pose from monocular image sequences is a challenging
and important research topic with numerous applications. Although current methods are …

Census data mining has great potential both in business development and in good public
policy, but still must be solved in this field a number of research issues. In this paper …

Recently there has been growing interest both to extend ILP to description logics and to
apply it to knowledge discovery in databases. In this paper we present a novel approach to …

Agents in dynamic environments have to deal with world representations that change over
time. In order to allow agents to act autonomously and to make their decisions on a solid …

Spatial data mining has been identified as an important task for understanding and use of
spatial data-and knowledge-bases. In this paper, we present a new approach to discover …

During the last decade, data miners became aware of geographical data. Today, knowledge
discovery from geographic data is still an open research field but promises to be a solid …

In this paper we propose a method for the discovery of spatial association rules, that is,
association rules involving spatial relations among (spatial) objects. The method is based on …

Spatial data mining is a demanding field since huge amounts of spatial data have been
collected in various applications, ranging form Remote Sensing to GIS, Computer …

Georeferenced information is growing every day, and geographical information systems are
becoming crucial in many decision processes. As a consequence, extracting knowledge …

The discovery of spatial association rules is a core task in spatial data science projects and
focuses on extracting useful and meaningful spatial patterns and relationships from spatial …