ModularityGraphsCOMMUNITY DETECTIONTWITTERMany real-world systems can be modeled as directed networks, such as transportation, social, collaboration or vocabulary networks. However, direction is often neglected or even ignored in community detection algorithms. This is in particular the case on large ...
indicate [1] that greedoids were originally developed to give a unified approach to the optimality of various greedy algorithms known in combinatorial optimization. Such algorithms can be loosely characterized as having locally optimal strategy and no backtracking. Nowadays, researchers provide different ...
greedy modularity algorithm with incomplete solvers for the satisfiability problem and we establish an analogy between the cluster core group heuristic used in core groups graph clustering and a sampling of restart points on the Morse graph of a continuous optimization problem with the same local ...
Community structure via greedy optimization of modularity
M. Bakillah et al., "Geo-located community detection in Twitter with enhanced fast-greedy optimization of modularity: The case study of typhoon Haiyan," International Journal of Geographical Information Science, 2015.Bakillah, M.; Li, R.-Y.; Liang, S.H. Geo-located community detection in ...
Geo-located community detection in Twitter with enhanced fast-greedy optimization of modularity: the case study of typhoon Haiyan. International Journal of Geographical Information Science, 1- 22.Bakillah, M.; Li, R.-Y.; Liang, S.H. G...
Modularity maximizationCommunity detection remains up to this date a challenging combinatorial optimization problem which has received much attention from various scientific fields in recent years. Since the problem for community detection with modularity maximization is known to be NP-complete, many ...
Modularity maximizationCommunity detection remains up to this date a challenging combinatorial optimization problem which has received much attention from various scientific fields in recent years. Since the problem for community detection with modularity maximization is known to be NP-complete, many ...
This method is based on a block model where off-diagonal blocks are neglected, and identifies the core nodes as belonging to a subset that minimizes a certain objective function. Our main result is an algorithm that exactly solves that combinatorial optimization problem with a computational cost ...