Home // GEOProcessing 2018, The Tenth International Conference on Advanced Geographic Information Systems, Applications, and Services // View article
Authors:
Claus-Peter Rückemann
Keywords: Data-centric Knowledge Mining; Mapping Objects and Entities; Spatial Mapping and Visualisation; Knowledge Resources; Advanced Computing.
Abstract:
The research presented in this paper focusses on a new methodology for knowledge based mapping of objects and entities for creating new multi-dimensional context. The mapping to new context can improve complex knowledge mining, discovery, and decision making results. The new context increases the potential for creating new insights. The paper introduces the new methodology used with advanced knowledge mining and provides the results of the present research. Examples from an implementation and a case study on knowledge mining and spatial representations are given. The case study utilises commonly available unstructured data and creates new multi-disciplinary context, especially spatial mapping of entities and integration with data and advanced tools, which can be used for further analysis, e.g., automated and visual analysis. The methodology can employ integrated knowledge resources and services for mapping support and can be applied to any content from arbitrary disciplines. The results of the mapping to new context can be used for knowledge mining workflows, for gaining new insight, and for creating and further improving long-term knowledge resources. The methodology also supports automated learning processes. This research aims on creating required bases for these goals and for new practical mining procedures and algorithms.
Pages: 40 to 45
Copyright: Copyright (c) IARIA, 2018
Publication date: March 25, 2018
Published in: conference
ISSN: 2308-393X
ISBN: 978-1-61208-617-0
Location: Rome, Italy
Dates: from March 25, 2018 to March 29, 2018