Databases and Information Systems Commons^™

Identification Of Conceptual Neighborhoods And Topological Relations In Z2, Brendan P. Hall

Electronic Theses and Dissertations

Topological relations are an essential element of spatial queries and reasoning about spatial information. The predominant model for topological relations in geographic information systems—the 9-intersection—identifies sixteen different relations between groups of pixels (called raster regions) given a set of conditions restricting the composition of the regions interior and boundary. Several of these relations are dependent on the raster region sizes to be realized. An example, ‘Completely Inside' would require raster regions to be sufficiently different in size for one raster to entirely encompass the other. By developing an iterative computational model, this work generates conceptual neighborhood graphs that outlined …

A Qualitative Representation Of Spatial Scenes In R2 With Regions And Lines, Joshua Lewis

Electronic Theses and Dissertations

Regions and lines are common geographic abstractions for geographic objects. Collections of regions, lines, and other representations of spatial objects form a spatial scene, along with their relations. For instance, the states of Maine and New Hampshire can be represented by a pair of regions and related based on their topological properties. These two states are adjacent (i.e., they meet along their shared boundary), whereas Maine and Florida are not adjacent (i.e., they are disjoint).

A detailed model for qualitatively describing spatial scenes should capture the essential properties of a configuration such that a description of the represented objects …

A Hidden Markov Model For Matching Spatial Networks, Benoit Costes, Julien Perret

Journal of Spatial Information Science

Datasets of the same geographic space at different scales and temporalities are increasingly abundant, paving the way for new scientific research. These datasets require data integration, which implies linking homologous entities in a process called data matching that remains a challenging task, despite a quite substantial literature, because of data imperfections and heterogeneities. In this paper, we present an approach for matching spatial networks based on a hidden Markov model (HMM) that takes full benefit of the underlying topology of networks. The approach is assessed using four heterogeneous datasets (streets, roads, railway, and hydrographic networks), showing that the HMM algorithm …

Discovery Of Topological Constraints On Spatial Object Classes Using A Refined Topological Model, Ivan Majic, Elham Naghizade, Stephan Winter, Martin Tomko

Journal of Spatial Information Science

In a typical data collection process, a surveyed spatial object is annotated upon creation, and is classified based on its attributes. This annotation can also be guided by textual definitions of objects. However, interpretations of such definitions may differ among people, and thus result in subjective and inconsistent classification of objects. This problem becomes even more pronounced if the cultural and linguistic differences are considered. As a solution, this paper investigates the role of topology as the defining characteristic of a class of spatial objects. We propose a data mining approach based on frequent itemset mining to learn patterns in …

Modeling Trajectories With Recurrent Neural Networks, Hao Wu, Ziyang Chen, Weiwei Sun, Baihua Zheng, Wei Wang

Research Collection School Of Computing and Information Systems

Modeling trajectory data is a building block for many smart-mobility initiatives. Existing approaches apply shallow models such as Markov chain and inverse reinforcement learning to model trajectories, which cannot capture the long-term dependencies. On the other hand, deep models such as Recurrent Neura lNetwork (RNN) have demonstrated their strength of modeling variable length sequences. However, directly adopting RNN to model trajectories is not appropriate because of the unique topological constraints faced by trajectories. Motivated by these findings, we design two RNN-based models which can make full advantage of the strength of RNN to capture variable length sequence and meanwhile to …

Exploring The Human Body Space: A Geographical Information System Based Anatomical Atlas, Antonio Barbeito, Marco Painho, Pedro Cabral, João Goyri O'Neill

Journal of Spatial Information Science

Anatomical atlases allow mapping the anatomical structures of the human body. Early versions of these systems consisted of analogical representations with informative text and labeled images of the human body. With computer systems, digital versions emerged and the third and fourth dimensions were introduced. Consequently, these systems increased their efficiency, allowing more realistic visualizations with improved interactivity and functionality. The 4D atlases allow modeling changes over time on the structures represented. The anatomical atlases based on geographic information system (GIS) environments allow the creation of platforms with a high degree of interactivity and new tools to explore and analyze the …

Semantic Operators And Fixed-Point Theory In Logic Programming, Anthony K. Seda, Pascal Hitzler

Computer Science and Engineering Faculty Publications

We consider rather general operators mapping valuations to (sets of) valuations in the context of the semantics of logic programming languages. This notion generalizes several of the standard operators encountered in this subject and is inspired by earlier work of M.C. Fitting. The fixed points of such operators play a fundamental role in logic programming semantics by providing standard models of logic programs and also in determining the computability properties of these standard models. We discuss some of our recent work employing topological ideas, in conjunction with order theory, to establish methods by which one can find the fixed points …