TY - GEN
T1 - Parameterising the dynamics of inter-group conflict from real world data
AU - Turner, Liam D.
AU - Colombo, Gualtiero B.
AU - Whitaker, Roger M.
AU - Felmlee, Diane
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2018/6/26
Y1 - 2018/6/26
N2 - Generative modelling of inter-group relations enables probabilistic forecasting of possible conflict for scenarios where real-world data is sparse. In order for such models to have relevance and integrity, it is important to ensure that real-world data is used to parameterise the model and verify its characteristics. In this paper we investigate how real-world datasets can be mapped into generative model parameters concerning group structures and behaviours. We highlight the issues involved and present a framework for classifying potential data based on three attributes: (i) inter-group structure, (ii) inter-group actions and (iii) impact of actions. We argue that these attributes are fundamental for benchmarking and developing generative models in the context of limited existing data on inter-group interaction.
AB - Generative modelling of inter-group relations enables probabilistic forecasting of possible conflict for scenarios where real-world data is sparse. In order for such models to have relevance and integrity, it is important to ensure that real-world data is used to parameterise the model and verify its characteristics. In this paper we investigate how real-world datasets can be mapped into generative model parameters concerning group structures and behaviours. We highlight the issues involved and present a framework for classifying potential data based on three attributes: (i) inter-group structure, (ii) inter-group actions and (iii) impact of actions. We argue that these attributes are fundamental for benchmarking and developing generative models in the context of limited existing data on inter-group interaction.
UR - https://www.scopus.com/pages/publications/85050231928
UR - https://www.scopus.com/inward/citedby.url?scp=85050231928&partnerID=8YFLogxK
U2 - 10.1109/UIC-ATC.2017.8397421
DO - 10.1109/UIC-ATC.2017.8397421
M3 - Conference contribution
AN - SCOPUS:85050231928
T3 - 2017 IEEE SmartWorld Ubiquitous Intelligence and Computing, Advanced and Trusted Computed, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovation, SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI 2017 - Conference Proceedings
SP - 1
EP - 6
BT - 2017 IEEE SmartWorld Ubiquitous Intelligence and Computing, Advanced and Trusted Computed, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovation, SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI 2017 - Conference Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 IEEE SmartWorld Ubiquitous Intelligence and Computing, Advanced and Trusted Computed, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovation, SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI 2017
Y2 - 4 April 2017 through 8 April 2017
ER -