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  1. Proceedings of The First ACM SIGSPATIAL International Workshop on Computational Models of Place (COMP '13)
  2. A Framework for Discriminative Polygonal Place Scoping
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Identification of structural landmarks in a park using movement data collected in a location-based game
Extracting Semantics of Individual Places from Movement Data by Analyzing Temporal Patterns of Visits
Semantic place localization from narratives
A Framework for Discriminative Polygonal Place Scoping
Identifying Spatial Structure of Urban Functional Centers Using Travel Survey Data: A Case Study of Singapore
A method of Area of Interest and Shooting Spot Detection using Geo-tagged Photographs
Towards Platial Joins and Buffers in Place-Based GIS
A rule-based genetic algorithm for mapping route descriptions towards map representations
A Comparison of String Similarity Measures for Toponym Matching
Extracting Spatial Information From Place Descriptions

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A Framework for Discriminative Polygonal Place Scoping

Content Provider ACM Digital Library
Abstract In general, it is desirable to have automatic tools that identify places in spatial data and to describe their characteristics, creating high-level summaries for spatial datasets which are valuable for planners, scientists, and policy makers. In this paper, we present a methodology that identifies a set of places based on a user-defined notion of interestingness and then identifies the scope of each place. A spatial clustering approach is used for the first step. For the second step, polygons are used as models to describe the scope of a place---the spatial area the place occupies. A 2-step methodology is introduced to compute a set of polygons for a set of places with each space being characterized by the set of objects which occupy the particular space. In the first step, an algorithm called LDTR is introduced that tightens the convex hull of a set of spatial objects by removing larger triangles of its Delaunay triangulation, obtaining an initial polygon for each place. Next, a post processing algorithm PolyRepair is introduced that tightens polygons further by reducing the overlap between the generated polygons; the algorithm gives preference to tightening polygons that have a lot of overlap with other polygons as the goal is to keep polygon tightening to a minimum. Finally, the two novel algorithms are demonstrated and evaluated for an urban computing benchmark.
Starting Page 20
Ending Page 27
Page Count 8
File Format PDF
ISBN 9781450325356
DOI 10.1145/2534848.2534849
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2013-11-05
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Spatial data mining Determining space scope Deriving polygon models for k sets of spatial objects Deriving polygon models from delaunay triangulations
Content Type Text
Resource Type Article
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