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ISPRS Int. J. Geo-Inf. 2019, 8(2), 92; https://doi.org/10.3390/ijgi8020092

Function-Based Search of Place Using Theoretical, Empirical and Probabilistic Patterns

1
Department of Geoinformatics - Z_GIS, University of Salzburg, Schillerstr. 30, 5020 Salzburg, Austria
2
Department of Computer Science, School of Computing and Engineering, University of Huddersfield, Queensgate, Huddersfield HD1 3DH, UK
*
Author to whom correspondence should be addressed.
This paper is an extended version of our paper published in the 10th International Conference on Geographic Information Science (GIScience 2018), Melbourne, Australia, 29–31 August 2018
Received: 23 November 2018 / Revised: 24 January 2019 / Accepted: 13 February 2019 / Published: 16 February 2019
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Abstract

Searching for places rather than traditional keyword-based search represents significant challenges. The most prevalent method of addressing place-related queries is based on place names but has limited potential due to the vagueness of natural language and its tendency to lead to ambiguous interpretations. In previous work we proposed a system-oriented logic-based formalization of place that goes beyond place names by introducing composition patterns of place which enable function-based search of space. In this study, we introduce flexibility into these patterns in terms of what is included when describing the spatial composition of a place using two distinct approaches, based on modal and probabilistic logic. Additionally, we propose a novel automated process of extracting these patterns relying on both theoretical and empirical knowledge, using statistical and spatial analysis and statistical relational learning. The proposed methodology is exemplified through the use case of locating all areas within London that support shopping-related functionality. Results show that the newly introduced patterns can identify more relevant areas, additionally offering a more fine-grained representation of the level of support of the required functionality. View Full-Text
Keywords: functions; place; patterns; function-based search; place-based GIS; statistical relational learning; modal logic; probabilistic logic; Bayesian network functions; place; patterns; function-based search; place-based GIS; statistical relational learning; modal logic; probabilistic logic; Bayesian network
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Papadakis, E.; Baryannis, G.; Petutschnig, A.; Blaschke, T. Function-Based Search of Place Using Theoretical, Empirical and Probabilistic Patterns. ISPRS Int. J. Geo-Inf. 2019, 8, 92.

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