ASHMR_Based Spatial Data Mining for the Inter-connectivity among Geographical Multi-representations

Inter-connectivity maintenance among multi-representations exists as a foundational task in building multi-scale data model, however, the existing methods are still not satisfactory in practice. In this context, the paper considers that the inter-connectivity among multiple representations can be only achieved if the multi-scale model is capable of explicitly inter-relating them and dealing with their differences. So, this paper firstly explores the relation among multiple representations from the same entity, such as multi-semantic, multi-geometry, multi-attributes, hierarchical semantic relations and so on. Based on these, this paper proposes aggregation-based semantic hierarchical matching rules (ASHMR) as the basis of tackling inter-connectivity among multi-representations, and defines the available hierarchical semantic knowledge, namely semantically equal, semantically related and semantically irrelevant. According to different change among multi-representations from different types of objects, the applications and techniques of the corresponding hierarchy inter-connectivity matching criterion are explored. At last, taken the road intersections as examples, a case in point is given in details for describing the strategies of inter-connectivity maintenance, showing that this method is feasible to deal with inter-connectivity.