Showing papers by "Simon Scheider published in 2010"

Affordance-based categorization of road network data using a grounded theory of channel networks

Abstract: We propose a grounded ontological theory of channel networks to categorize features, such as junctions, in road network databases. The theory is grounded, because its primitives can be given an unambiguous interpretation into directly observable qualities of physical road networks, such as supported movements and their medium, connectedness of such media, and turnoff restrictions. The theory provides a very general approach to automatically annotate and integrate road network data from heterogeneous sources, because it rests on application-independent observation principles. We suggest that road network categories such as junctions and roads are based on locomotion affordances. Road network databases can be mapped into our channel network theory, so that instances of roads and junctions can be automatically categorized or checked for consistency by what they afford. In this paper, we introduce affordance-based definitions of a road network and a junction, and show that the definition of latter is satisfied by some of the most common junction types.

Constructing Bodies and their Qualities from Observations

Abstract: The principle challenge for information semantics lies in the degrees of freedom to interpret symbols in terms of thoughts and experiences which leads to incompatible views on the world. Consequently, incompatible information ontologies and interpretations of the described data will remain. Even though there is usually a common experiential ground, it stays often unknown to users of semantically annotated data. This symbol grounding problem is a bottleneck of information semantics, which remains largely unsolved in ontological practice. In this paper, we suggest --in the spirit of Jeremy Bentham --to introduce formal primitives which are directly grounded in inter-subjective experience, and which serve to expose and construct complex qualities in information ontologies.

Spatial Data Mining in Practice: Principles and Case Studies

Abstract: Almost any data can be referenced in geographic space. Such data permit advanced analyses that utilize the position and relationships of objects in space as well as geographic background information. Even though spatial data mining is still a young research discipline, in the past years research advances have shown that the particular challenges of spatial data can be mastered and that the technology is ready for practical application when spatial aspects are treated as an integrated part of data mining and model building. In this chapter in particular, we give a detailed description of several customer projects that we have carried out and which all involve customized data mining solutions for business relevant tasks. The applications range from customer segmentation to the prediction of traffic frequencies and the analysis of GPS trajectories. They have been selected to demonstrate key challenges, to provide advanced solutions and to arouse further research questions.