most citedPredictive Situation Awareness for Ebola Virus Disease using a Collective Intelligence Multi-Model Integration Platform: Bayes Cloud

1 citations · 1 across the 2 of their papers we have counts for

collaborators

6 papers

cs.LG2019

A Study of Machine Learning Models in Predicting the Intention of Adolescents to Smoke Cigarettes

Seung Joon Nam, Han Min Kim, Thomas Kang +1

The use of electronic cigarette (e-cigarette) is increasing among adolescents. This is problematic since consuming nicotine at an early age can cause harmful effects in developing…

cs.AI20191 cited

Predictive Situation Awareness for Ebola Virus Disease using a Collective Intelligence Multi-Model Integration Platform: Bayes Cloud

Cheol Young Park, Shou Matsumoto, Jubyung Ha +1

The humanity has been facing a plethora of challenges associated with infectious diseases, which kill more than 6 million people a year. Although continuous efforts have been appli…

cs.AI2018

Reference Model of Multi-Entity Bayesian Networks for Predictive Situation Awareness

Cheol Young Park, Kathryn Blackmond Laskey

During the past quarter-century, situation awareness (SAW) has become a critical research theme, because of its importance. Since the concept of SAW was first introduced during Wor…

cs.LG2018

MEBN-RM: A Mapping between Multi-Entity Bayesian Network and Relational Model

Cheol Young Park, Kathryn Blackmond Laskey

Multi-Entity Bayesian Network (MEBN) is a knowledge representation formalism combining Bayesian Networks (BN) with First-Order Logic (FOL). MEBN has sufficient expressive power for…

cs.LG2018

Human-aided Multi-Entity Bayesian Networks Learning from Relational Data

Cheol Young Park, Kathryn Blackmond Laskey

An Artificial Intelligence (AI) system is an autonomous system which emulates human mental and physical activities such as Observe, Orient, Decide, and Act, called the OODA process…

cs.AI2018

Gaussian Mixture Reduction for Time-Constrained Approximate Inference in Hybrid Bayesian Networks

Cheol Young Park, Kathryn Blackmond Laskey, Paulo C. G. Costa +1

Hybrid Bayesian Networks (HBNs), which contain both discrete and continuous variables, arise naturally in many application areas (e.g., image understanding, data fusion, medical di…