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About Situation-Aware Deep Reinforcement Learning Link Prediction Model For Evolving Criminal Networks
This document proposes a deep reinforcement learning model called FDRL-CNA to predict links in criminal networks. FDRL-CNA incorporates metadata like arrest records alongside a time-evolving criminal network dataset. It is compared to a baseline TDRL-CNA model that does not include metadata fusion. Experimental results show FDRL-CNA has higher predictive accuracy for new and recurrent links, demonstrating the benefit of combining network structure data with external metadata for link prediction in criminal networks.
Detailed Information
Author: | ['Magin Edgard Madrid Castillo'] |
---|---|
Publication Year: | 2022 |
Pages: | 10 |
Language: | English |
Format: | |
Price: | FREE |
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