Time-sensitive behavior prediction in a health social network

Amnay Amimeur, Nhat Hai Phan, Dejing Dou, David Kil, Brigitte Piniewski

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Human behavior prediction is critical in understanding and addressing large scale health and social issues in online communities. Specifically, predicting when in the future a user will engage in a behavior as opposed to whether a user will behave at a particular time is a less studied subproblem of behavior prediction. Further lacking is exploration of how social context affects personal behavior and the exploitation of network structure information in behavior and time prediction. To address these problems we propose a novel semi-supervised deep learning model for prediction of return time to personal behavior. A carefully designed objective function ensures the model learns good social context embeddings and historical behavior embeddings in order to capture the effects of social influence on personal behavior. Our model is validated on a unique health social network dataset by predicting when users will engage in physical activities. We show our model outperforms relevant time prediction baselines.

Original languageEnglish (US)
Title of host publicationProceedings - 16th IEEE International Conference on Machine Learning and Applications, ICMLA 2017
EditorsXuewen Chen, Bo Luo, Feng Luo, Vasile Palade, M. Arif Wani
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1083-1088
Number of pages6
ISBN (Electronic)9781538614174
DOIs
StatePublished - Jan 1 2017
Event16th IEEE International Conference on Machine Learning and Applications, ICMLA 2017 - Cancun, Mexico
Duration: Dec 18 2017Dec 21 2017

Publication series

NameProceedings - 16th IEEE International Conference on Machine Learning and Applications, ICMLA 2017
Volume2017-December

Other

Other16th IEEE International Conference on Machine Learning and Applications, ICMLA 2017
CountryMexico
CityCancun
Period12/18/1712/21/17

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Science Applications

Keywords

  • Behavior Prediction
  • Deep Learning
  • Graph Embedding
  • Social Network Analysis

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