A large number of clustering approaches have been proposed for the analysis of gene
expression data obtained from microarray experiments. However, the results from the …

Many real‐world networks are intimately organized according to a community structure.
Much research effort has been devoted to develop methods and algorithms that can …

This paper introduces a product quantization-based approach for approximate nearest
neighbor search. The idea is to decompose the space into a Cartesian product of low …

In these lecture notes, the authors have outlined several approaches to solve a NMF/NTF
problem. The following main conclusions can be drawn: 1) Multiplicative algorithms are not …

As a prolific research area in data mining, subspace clustering and related problems
induced a vast quantity of proposed solutions. However, many publications compare a new …

Nonnegative matrix approximation (NNMA) is a recent technique for dimensionality
reduction and data analysis that yields a parts based, sparse nonnegative representation for …

In recent years, the explosive growth of online media, such as blogs and social networking
sites, has enabled individuals and organizations to write about their personal experiences …

Cluster or co-cluster analyses are important tools in a variety of scientific areas. The
introduction of this book presents a state of the art of already well-established, as well as …

Co-clustering is a powerful data mining technique with varied applications such as text
clustering, microarray analysis and recommender systems. Recently, an information …

The nonnegative matrix factorization (NMF) has been shown recently to be useful for
clustering and various extensions and variations of NMF have been proposed recently …