A hierarchical RL dialogue system that asks knowledge-graph-derived questions detects simulated identity fraud more accurately than rule-based baselines, but all results hinge on a user simulator calibrated from only 31 volunteers.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CL 1years
2019 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Are You for Real? Detecting Identity Fraud via Dialogue Interactions
A hierarchical RL dialogue system that asks knowledge-graph-derived questions detects simulated identity fraud more accurately than rule-based baselines, but all results hinge on a user simulator calibrated from only 31 volunteers.