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What matters the most? Optimal Quick Classification of Urban Issue Reports by Importance

Abstract: 

Civic engagement platforms such as SeeClickFix and FixMyStreet have revolutionized the way citizens interact with local governments to report and resolve urban issues. However, recognizing which urban issues are important to the community in an accurate and timely manner is essential for authorities to prioritize important issues, allocate resources and maintain citizens’ satisfaction with local governments. To this end, a novel formulation based on optimal stopping theory is devised to infer urban issues importance from ambiguous textual, time and location information. The goal is to optimize recognition accuracy, while minimizing the time to reach a decision. The optimal classification and stopping rules are derived. Furthermore, a near–real–time urban issue reports processing method to infer the importance of incoming issues is proposed. The effectiveness of the proposed method is illustrated on a real–word dataset from SeeClick-Fix, where significant reduction in time–to–decision without sacrificing accuracy is observed.

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Paper Details

Authors:
Yasitha Liyanage, Mengfan Yao, Christopher Yong, Daphney-Stavroula Zois, Charalampos Chelmis
Submitted On:
19 November 2018 - 3:29pm
Short Link:
Type:
Presentation Slides
Event:
Presenter's Name:
Yasitha Liyanage
Paper Code:
GS-L.5.4
Document Year:
2018
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Document Files

SCC_Final.pdf

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[1] Yasitha Liyanage, Mengfan Yao, Christopher Yong, Daphney-Stavroula Zois, Charalampos Chelmis, "What matters the most? Optimal Quick Classification of Urban Issue Reports by Importance", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3688. Accessed: Aug. 25, 2019.
@article{3688-18,
url = {http://sigport.org/3688},
author = {Yasitha Liyanage; Mengfan Yao; Christopher Yong; Daphney-Stavroula Zois; Charalampos Chelmis },
publisher = {IEEE SigPort},
title = {What matters the most? Optimal Quick Classification of Urban Issue Reports by Importance},
year = {2018} }
TY - EJOUR
T1 - What matters the most? Optimal Quick Classification of Urban Issue Reports by Importance
AU - Yasitha Liyanage; Mengfan Yao; Christopher Yong; Daphney-Stavroula Zois; Charalampos Chelmis
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3688
ER -
Yasitha Liyanage, Mengfan Yao, Christopher Yong, Daphney-Stavroula Zois, Charalampos Chelmis. (2018). What matters the most? Optimal Quick Classification of Urban Issue Reports by Importance. IEEE SigPort. http://sigport.org/3688
Yasitha Liyanage, Mengfan Yao, Christopher Yong, Daphney-Stavroula Zois, Charalampos Chelmis, 2018. What matters the most? Optimal Quick Classification of Urban Issue Reports by Importance. Available at: http://sigport.org/3688.
Yasitha Liyanage, Mengfan Yao, Christopher Yong, Daphney-Stavroula Zois, Charalampos Chelmis. (2018). "What matters the most? Optimal Quick Classification of Urban Issue Reports by Importance." Web.
1. Yasitha Liyanage, Mengfan Yao, Christopher Yong, Daphney-Stavroula Zois, Charalampos Chelmis. What matters the most? Optimal Quick Classification of Urban Issue Reports by Importance [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3688