Motivated by the above observations, this paper proposes a Hierarchical High-order Co-Clustering algorithm by maximizing Modularity (MHCoC). MHCoC chooses the modularity in the co-clustering context as a quality evaluation indicator, and an efficient iterative algorithm is designed to optimize the objective function.
Jul 23, 2021
A new solution, a Hierarchical High-order Co-clustering Algorithm by Maximizing Modularity, MHCoC, is presented, which iteratively optimizes the objective ...
In this paper, we study the problem of co-clustering of star-structured high-order heterogeneous data. We present a new solution, a Hierarchical High-order Co- ...
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We present a new solution, a Hierarchical High-order Co-clustering Algorithm by Maximizing Modularity, MHCoC, which iteratively optimizes the objective function ...
Gao B, Liu T, Ma W (2006) Star-structured high-order heterogeneous data co-clustering based on consistent information theory, In: Proc. 6th ACM Int. Conf. Data ...
Building on recent advancements, the study by Wei et al. [45] introduces a hierarchical high-order co-clustering algorithm that maximizes modularity. This ...
Aug 23, 2021 · ... a new solution, a Hierarchical High-order Co-clustering Algorithm by Maximizing Modularity, MHCoC, which iteratively optimizes the objective
Alert. Hierarchical high-order co-clustering algorithm by maximizing modularity ... 4 Excerpts. Hierarchical Clustering via Sketches and Hierarchical Correlation ...
In this paper, an agglomerative hierarchical co-clustering algorithm based on Bregman divergence is proposed to learn hierarchical structure of multiple ...
Oct 1, 2016 · In this paper we show how the modularity measure can serve as a useful criterion for co-clustering document-term matrices.