TY - GEN
T1 - Inferring users' usage patterns for drug abuse surveillance
AU - Liu, Ruoran
AU - Li, Qiudan
AU - Dajun Zeng, Daniel
N1 - Funding Information:
This work was supported by the National Key R&D Program of China under Grant No. 2016QY02D0305, the National Natural Science Foundation of China under Grant No. 61671450, 71621002, the Key Research Program of the Chinese Academy of Sciences under Grant No. ZDRW-XH-2017-3.
Funding Information:
ACKNOWLEDGMENT This work was supported by the National Key R&D Program of China under Grant No. 2016QY02D0305, the National Natural Science Foundation of China under Grant No. 61671450, 71621002, the Key Research Program of the Chinese Academy of Sciences under Grant No. ZDRW-XH-2017-3.
Publisher Copyright:
© 2019 IEEE.
PY - 2019/7
Y1 - 2019/7
N2 - 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.
AB - 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.
KW - Drug Abuse Surveillance
KW - Interaction relationship
KW - Semantic information
KW - Usage Patterns Inference
UR - http://www.scopus.com/inward/record.url?scp=85072986003&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85072986003&partnerID=8YFLogxK
U2 - 10.1109/ISI.2019.8823475
DO - 10.1109/ISI.2019.8823475
M3 - Conference contribution
AN - SCOPUS:85072986003
T3 - 2019 IEEE International Conference on Intelligence and Security Informatics, ISI 2019
SP - 134
EP - 136
BT - 2019 IEEE International Conference on Intelligence and Security Informatics, ISI 2019
A2 - Zheng, Xiaolong
A2 - Abbasi, Ahmed
A2 - Chau, Michael
A2 - Wang, Alan
A2 - Zhou, Lina
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 17th IEEE International Conference on Intelligence and Security Informatics, ISI 2019
Y2 - 1 July 2019 through 3 July 2019
ER -