TY - JOUR
T1 - GeoCAM
T2 - A geovisual analytics workspace to contextualize and interpret statements about movement
AU - Jaiswal, Anuj
AU - Pezanowski, Scott
AU - Mitra, Prasenjit
AU - Zhang, Xiao
AU - Xu, Sen
AU - Turton, Ian
AU - Klippel, Alexander
AU - MacEachren, Alan M.
N1 - Publisher Copyright:
© By the author(s).
PY - 2011
Y1 - 2011
N2 - This article focuses on integrating computational and visual methods in a system that supports analysts to identify, extract, map, and relate linguistic accounts of movement. We address two objectives: (1) build the conceptual, theoretical, and empirical framework needed to represent and interpret human-generated directions; and (2) design and implement a geovisual analytics workspace for direction document analysis. We have built a set of geo-enabled, computational methods to identify documents containing movement statements, and a visual analytics environment that uses natural language processing methods iteratively with geographic database support to extract, interpret, and map geographic movement references in context. Additionally, analysts can provide feedback to improve computational results. To demonstrate the value of this integrative approach, we have realized a proof-of-concept implementation focusing on identifying and processing documents that contain human-generated route directions. Using our visual analytic interface, an analyst can explore the results, provide feedback to improve those results, pose queries against a database of route directions, and interactively represent the route on a map.
AB - This article focuses on integrating computational and visual methods in a system that supports analysts to identify, extract, map, and relate linguistic accounts of movement. We address two objectives: (1) build the conceptual, theoretical, and empirical framework needed to represent and interpret human-generated directions; and (2) design and implement a geovisual analytics workspace for direction document analysis. We have built a set of geo-enabled, computational methods to identify documents containing movement statements, and a visual analytics environment that uses natural language processing methods iteratively with geographic database support to extract, interpret, and map geographic movement references in context. Additionally, analysts can provide feedback to improve computational results. To demonstrate the value of this integrative approach, we have realized a proof-of-concept implementation focusing on identifying and processing documents that contain human-generated route directions. Using our visual analytic interface, an analyst can explore the results, provide feedback to improve those results, pose queries against a database of route directions, and interactively represent the route on a map.
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U2 - 10.5311/JOSIS.2011.3.55
DO - 10.5311/JOSIS.2011.3.55
M3 - Article
AN - SCOPUS:84901416159
SN - 1948-660X
VL - 3
SP - 65
EP - 101
JO - Journal of Spatial Information Science
JF - Journal of Spatial Information Science
IS - 2011
ER -