Drug Abuse Detection via Broad Learning

Prescription drug abuse is one of the fastest growing public health problems in the USA. This work develops a broad learning method for Drug Abuse Detection (DAD). In this paper, we propose a new broad learning-based method named ILSTM, short for Improved Long Short-Term Memory, to study the data fusion and prediction from heterogeneous data sources for DAD. The algorithm utilizes the broad learning framework to handle data fusion broadly and information mining deeply simultaneously. Moreover, the effectiveness and prevalence of Holt-Winter inspire our work in the temporal property for DAD.

[1]  Xintao Wu,et al.  Using Loglinear Model for Discrimination Discovery and Prevention , 2016, 2016 IEEE International Conference on Data Science and Advanced Analytics (DSAA).

[2]  Poonam N. Railkar,et al.  Long-Term and Short-Term Traffic Forecasting Using Holt-Winters Method: A Comparability Approach with Comparable Data in Multiple Seasons , 2017, Int. J. Synth. Emot..

[3]  Lizhen Xu,et al.  CNN-BiLSTM-CRF Model for Term Extraction in Chinese Corpus , 2018, WISA.

[4]  Nicholas Genes,et al.  Leveraging Social Networks for Toxicovigilance , 2013, Journal of Medical Toxicology.

[5]  Claudio Meneses Villegas,et al.  Sentiment analysis and opinion mining applied to scientific paper reviews , 2019, Intell. Data Anal..

[6]  Lei Zheng,et al.  Deep and Broad Learning on Content-Aware POI Recommendation , 2017, 2017 IEEE 3rd International Conference on Collaboration and Internet Computing (CIC).

[7]  Philip S. Yu,et al.  BL-MNE: Emerging Heterogeneous Social Network Embedding Through Broad Learning with Aligned Autoencoder , 2017, 2017 IEEE International Conference on Data Mining (ICDM).

[8]  André Panisson,et al.  Firsthand Opiates Abuse on Social Media: Monitoring Geospatial Patterns of Interest Through a Digital Cohort , 2019, WWW.

[9]  Jeremy Ginsberg,et al.  Detecting influenza epidemics using search engine query data , 2009, Nature.

[10]  Soon Ae Chun,et al.  Deep Learning Model for Classifying Drug Abuse Risk Behavior in Tweets , 2018, 2018 IEEE International Conference on Healthcare Informatics (ICHI).

[11]  Philip S. Yu,et al.  HitFraud: A Broad Learning Approach for Collective Fraud Detection in Heterogeneous Information Networks , 2017, 2017 IEEE International Conference on Data Mining (ICDM).

[12]  Bin Wu,et al.  Complaint Classification Using Hybrid-Attention GRU Neural Network , 2019, PAKDD.