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When Urban Safety Index Inference Meets Location-Based Data
Zhe Peng
, Yuan Yao
, Bin Xiao
*
, Songtao Guo
, Yuanyuan Yang
*
Corresponding author for this work
Department of Computer Science
Research output
:
Contribution to journal
›
Journal article
›
peer-review
12
Citations (Scopus)
Overview
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Dive into the research topics of 'When Urban Safety Index Inference Meets Location-Based Data'. Together they form a unique fingerprint.
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Computer Science
Global Positioning System
100%
Route Planning
100%
Data Source
100%
Discriminative Feature
100%
Evaluation Result
100%
Granularity
100%
Analysis System
100%
Points of Interest
100%
Related Feature
100%
Police Station
100%
Keyphrases
Location Information
100%
Safety Index
100%
Urban Safety
100%
Urban Places
33%
Safety Analysis
33%
Learning Methods
16%
Route Planning
16%
Discriminative Feature Representation
16%
Granularity
16%
Cross-domain
16%
Evaluation Results
16%
Co-training
16%
Training Base
16%
New York City
16%
Police Station
16%
Feature Correlation
16%
Crime Events
16%
Walking Routes
16%
Density Population
16%
Sparse Autoencoder
16%
Taxi GPS Trajectories
16%
Housing Rent
16%
Correlation Constraint
16%
Housing Density
16%
Urban Maps
16%
Event Record
16%
Safe Walking
16%
Engineering
Safety Index
100%
Safety Analysis
33%
Granularity
16%
Real Data
16%
Global Positioning System
16%
Great Importance
16%
Data Source
16%
Route Planning
16%