Inferring users' usage patterns for drug abuse surveillance

Ruoran Liu; Qiudan Li; Daniel Dajun Zeng

doi:10.1109/ISI.2019.8823475

Inferring users' usage patterns for drug abuse surveillance

Ruoran Liu, Qiudan Li, Daniel Dajun Zeng

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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.

Original language	English (US)
Title of host publication	2019 IEEE International Conference on Intelligence and Security Informatics, ISI 2019
Editors	Xiaolong Zheng, Ahmed Abbasi, Michael Chau, Alan Wang, Lina Zhou
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	134-136
Number of pages	3
ISBN (Electronic)	9781728125046
DOIs	https://doi.org/10.1109/ISI.2019.8823475
State	Published - Jul 2019
Externally published	Yes
Event	17th IEEE International Conference on Intelligence and Security Informatics, ISI 2019 - Shenzhen, China Duration: Jul 1 2019 → Jul 3 2019

Publication series

Name	2019 IEEE International Conference on Intelligence and Security Informatics, ISI 2019

Conference

Conference	17th IEEE International Conference on Intelligence and Security Informatics, ISI 2019
Country	China
City	Shenzhen
Period	7/1/19 → 7/3/19

Keywords

Drug Abuse Surveillance
Interaction relationship
Semantic information
Usage Patterns Inference

ASJC Scopus subject areas

Safety, Risk, Reliability and Quality
Computer Vision and Pattern Recognition
Information Systems and Management
Information Systems

Access to Document

10.1109/ISI.2019.8823475

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Cite this

Liu, R., Li, Q., & Dajun Zeng, D. (2019). Inferring users' usage patterns for drug abuse surveillance. In X. Zheng, A. Abbasi, M. Chau, A. Wang, & L. Zhou (Eds.), 2019 IEEE International Conference on Intelligence and Security Informatics, ISI 2019 (pp. 134-136). [8823475] (2019 IEEE International Conference on Intelligence and Security Informatics, ISI 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISI.2019.8823475

Inferring users' usage patterns for drug abuse surveillance. / Liu, Ruoran; Li, Qiudan; Dajun Zeng, Daniel.

2019 IEEE International Conference on Intelligence and Security Informatics, ISI 2019. ed. / Xiaolong Zheng; Ahmed Abbasi; Michael Chau; Alan Wang; Lina Zhou. Institute of Electrical and Electronics Engineers Inc., 2019. p. 134-136 8823475 (2019 IEEE International Conference on Intelligence and Security Informatics, ISI 2019).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Liu, R, Li, Q & Dajun Zeng, D 2019, Inferring users' usage patterns for drug abuse surveillance. in X Zheng, A Abbasi, M Chau, A Wang & L Zhou (eds), 2019 IEEE International Conference on Intelligence and Security Informatics, ISI 2019., 8823475, 2019 IEEE International Conference on Intelligence and Security Informatics, ISI 2019, Institute of Electrical and Electronics Engineers Inc., pp. 134-136, 17th IEEE International Conference on Intelligence and Security Informatics, ISI 2019, Shenzhen, China, 7/1/19. https://doi.org/10.1109/ISI.2019.8823475

Liu R, Li Q, Dajun Zeng D. Inferring users' usage patterns for drug abuse surveillance. In Zheng X, Abbasi A, Chau M, Wang A, Zhou L, editors, 2019 IEEE International Conference on Intelligence and Security Informatics, ISI 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 134-136. 8823475. (2019 IEEE International Conference on Intelligence and Security Informatics, ISI 2019). https://doi.org/10.1109/ISI.2019.8823475

Liu, Ruoran ; Li, Qiudan ; Dajun Zeng, Daniel. / Inferring users' usage patterns for drug abuse surveillance. 2019 IEEE International Conference on Intelligence and Security Informatics, ISI 2019. editor / Xiaolong Zheng ; Ahmed Abbasi ; Michael Chau ; Alan Wang ; Lina Zhou. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 134-136 (2019 IEEE International Conference on Intelligence and Security Informatics, ISI 2019).

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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.",

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