For this purpose, we have enhanced the fast-greedy optimization of modularity (FGM) clustering algorithm with semantic similarity so that it can deal with the complex social graphs extracted from Twitter. Then, we have coupled the enhanced FGM with the varied density-based spatial clustering of ...
Here we consider a scheme based on a standard “greedy” optimization algorithm, which appears to perform well. Our algorithm falls in the general category of agglomerative hierarchical clustering methods [15, 16]. Starting with a state in which each vertex is the sole member of one of n ...
In their model, a one-pass partitioning algorithm can pass multiple times through the entire input while the edge-cut is iteratively reduced. The authors propose ReLDG and ReFennel, which are respective restreaming adaptations of linear deterministic greedy [14] (LDG) and Fennel [4]. On the ...
CNM is a modularity optimization algorithm designed to directly optimize the modularity quality function Q w , and hence, it is no surprise that it performed best with this function, as shown in Table 8. The modularity maximization process of CNM [23] yields a partitioning containing one very ...
Global optimization of cerebral cortex layout. Proc. Natl Acad. Sci. USA 101, 1081–1086 (2004). Article ADS CAS PubMed Central Google Scholar Langford, J. & Zhang, T. The Epoch-Greedy algorithm for multi-armed bandits with side information. In Advances in Neural Information Processing ...
prove that the optimization problem is NP-hard6, present a greedy approximation algorithm applicable to all three models, which guarantees that the influence spread is within (1 − 1/e) of the optimal influence spread. Then, they propose a propagation-based algorithm (called general ...
Unfortunately, this greedy algorithm may Fast unfolding of communities in large networks 3 Figure 1. Visualization of the steps of our algorithm. Each pass is made of two phases: one where modularity is optimized by allowing only local changes of communities; one where the found communities are ...
5、ve been proposed aiming at different kinds of large scale complex networksIn this paper, we based on greedy algorithm,According to a condensation algorithm which Newman in designed.the GN algorithm on optimization-Fast Newman algorithm.We decomposition a variety of complex network community struct...
Unfortunately, this greedy algorithm may Fast unfolding of communities in large networks 3 Figure 1. Visualization of the steps of our algorithm. Each pass is made of two phases: one where modularity is optimized by allowing only local changes of communities; one where the found communities are ...
[6], Gibbs Sampler [7], AlignACE [8], PROJECTION [9], and CRMD [10] belong to this group. These algorithms use optimization techniques from the fields of statistics and machine learning, including the greedy strategy [5], the Expectation-Maximization method [6], Gibbs sampling methods [...