Paper Info
Title
Distributed Heuristics for Optimizing Cohesive Groups: A Support for Clinical Patient Engagement in Social Network Analysis
Abstract
Social interaction allows to support the disease management by creating online spaces where patients can interact with clinicians, and share experiences with other patients. Therefore, promoting targeted communication in online social spaces is a means to group patients around shared goals, offer emotional support, and finally engage patients in their healthcare decision making process. In this paper, we approach the argument from a theoretical perspective: we design an optimization problem aimed to encourage the creation of (induced) sub-networks of patients which, being recently diagnosed, wish to deepen the knowledge about their medical treatment with some other similar profiled patients, which have already been followed up by specific (even alternative) care centers. In particular, due to the computational hardness of the proposed problem, we provide approximated solutions based on distributed heuristics (i.e., Genetic Algorithms). Results are given for simulated data using Erdos-Renyi random graphs.
Year
DOI
Venue
2018
10.1109/PDP2018.2018.00044
2018 26th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP)
Keywords
Field
DocType
Distributed Heuristic,Genetic Algorithm,Dense Communities,2-club optimization problem
Health care,Social relation,Random graph,Computer science,Social network analysis,Knowledge management,Heuristics,Optimization problem,Genetic algorithm,Decision-making,Distributed computing
Conference
ISSN
ISBN
Citations 
1066-6192
978-1-5386-4976-3
0
PageRank 
References 
Authors
0.34
13
5
Name
Order
Citations
PageRank
Italo Zoppis13818.39
Riccardo Dondi28918.42
Davide Coppetti300.34
Alessandro Beltramo400.34
Giancarlo Mauri52106297.38