Inferring Users’ Usage Patterns for Drug Abuse Surveillance

Abstract

Inferring drug usage patterns includes age of drug abuse and intention of rehabilitation, which is of much importance for drug abuse surveillance. The challenges are how to mine patterns from posts and interaction relationships between users. In this paper, we propose a novel drug usage pattern inference method, which improves the inference accuracy by integrating the semantic features and interaction relationships effectively. Experimental results on a real-world dataset demonstrate the efficacy of the proposed method.