Abstract
Automatic and accurate extraction of destinations in human-generated route descriptions facilitates visualizing text route descriptions on digital maps. Such information further supports research aiming at understanding human cognition of geospatial information. However, as reproted in previous work, the recognition of destinations is not satisfactory. In this paper, we show our approach and achievements in improving the accuracy of destination name recognition. We identified and evaluated multiple features for classifying a named entity to be either "destination" or "non- destination"; after that, we use a simple yet effective post-processing algorithm to improve classification accuracy. Comprehensive experiments confirm the effectiveness of our approach.
| Original language | English |
|---|---|
| Title of host publication | GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems |
| Pages | 373-376 |
| Number of pages | 4 |
| DOIs | |
| Publication status | Published - 2011 |
| Externally published | Yes |
| Event | 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2011 - Chicago, IL Duration: 1 Nov 2011 → 4 Nov 2011 |
Other
| Other | 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2011 |
|---|---|
| City | Chicago, IL |
| Period | 1/11/11 → 4/11/11 |
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Keywords
- destination name classification
- driving directions
- geospatial information extraction
ASJC Scopus subject areas
- Earth-Surface Processes
- Computer Science Applications
- Modelling and Simulation
- Computer Graphics and Computer-Aided Design
- Information Systems
Cite this
Identifying destinations automatically from human generated route directions. / Zhang, Xiao; Mitra, Prasenjit; Klippel, Alexander; MacEachren, Alan M.
GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems. 2011. p. 373-376.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Identifying destinations automatically from human generated route directions
AU - Zhang, Xiao
AU - Mitra, Prasenjit
AU - Klippel, Alexander
AU - MacEachren, Alan M.
PY - 2011
Y1 - 2011
N2 - Automatic and accurate extraction of destinations in human-generated route descriptions facilitates visualizing text route descriptions on digital maps. Such information further supports research aiming at understanding human cognition of geospatial information. However, as reproted in previous work, the recognition of destinations is not satisfactory. In this paper, we show our approach and achievements in improving the accuracy of destination name recognition. We identified and evaluated multiple features for classifying a named entity to be either "destination" or "non- destination"; after that, we use a simple yet effective post-processing algorithm to improve classification accuracy. Comprehensive experiments confirm the effectiveness of our approach.
AB - Automatic and accurate extraction of destinations in human-generated route descriptions facilitates visualizing text route descriptions on digital maps. Such information further supports research aiming at understanding human cognition of geospatial information. However, as reproted in previous work, the recognition of destinations is not satisfactory. In this paper, we show our approach and achievements in improving the accuracy of destination name recognition. We identified and evaluated multiple features for classifying a named entity to be either "destination" or "non- destination"; after that, we use a simple yet effective post-processing algorithm to improve classification accuracy. Comprehensive experiments confirm the effectiveness of our approach.
KW - destination name classification
KW - driving directions
KW - geospatial information extraction
UR - http://www.scopus.com/inward/record.url?scp=84863028577&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84863028577&partnerID=8YFLogxK
U2 - 10.1145/2093973.2094026
DO - 10.1145/2093973.2094026
M3 - Conference contribution
SN - 9781450310314
SP - 373
EP - 376
BT - GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems
ER -