Triclustering algorithms for three-dimensional data analysis: a comprehensive survey

R Henriques, SC Madeira - ACM Computing Surveys (CSUR), 2018‏ - dl.acm.org
Three-dimensional data are increasingly prevalent across biomedical and social domains.
Notable examples are gene-sample-time, individual-feature-time, or node-node-time data …

Multi-view clustering via joint nonnegative matrix factorization

J Liu, C Wang, J Gao, J Han - Proceedings of the 2013 SIAM international …, 2013‏ - SIAM
Many real-world datasets are comprised of different representations or views which often
provide information complementary to each other. To integrate information from multiple …

Parameter-less co-clustering for star-structured heterogeneous data

D Ienco, C Robardet, RG Pensa, R Meo - Data Mining and Knowledge …, 2013‏ - Springer
The availability of data represented with multiple features coming from heterogeneous
domains is getting more and more common in real world applications. Such data represent …

Cross-platform emerging topic detection and elaboration from multimedia streams

BK Bao, C Xu, W Min, MS Hossain - ACM Transactions on Multimedia …, 2015‏ - dl.acm.org
With the explosive growth of online media platforms in recent years, it becomes more and
more attractive to provide users a solution of emerging topic detection and elaboration. And …

Hierarchical high-order co-clustering algorithm by maximizing modularity

J Wei, H Ma, Y Liu, Z Li, N Li - International Journal of Machine Learning …, 2021‏ - Springer
The star-structured high-order heterogeneous data is ubiquitous, such data represent
objects of a certain type, connected to other types of data, or the features, so that the overall …

Discovering High-Level Performance Models for Ticket Resolution Processes: (Short Paper)

F Folino, M Guarascio, L Pontieri - … " On the Move to Meaningful Internet …, 2013‏ - Springer
Predicting run-time performances is a hot issue in ticket resolution processes. Recent efforts
to take account for the sequence of resolution steps, suggest that predictive Process Mining …

Clustering and integrating of heterogeneous microbiome data by joint symmetric nonnegative matrix factorization with laplacian regularization

Y Ma, X Hu, T He, X Jiang - IEEE/ACM Transactions on …, 2017‏ - ieeexplore.ieee.org
Many datasets that exists in the real world are often comprised of different representations or
views which provide complementary information to each other. To integrate information from …

Distributed MCMC inference for Bayesian Non-Parametric Latent Block Model

R Khoufache, A Belhadj, H Azzag… - Pacific-Asia Conference on …, 2024‏ - Springer
In this paper, we introduce a novel Distributed Markov Chain Monte Carlo (MCMC) inference
method for the Bayesian Non-Parametric Latent Block Model (DisNPLBM), employing the …

Multi-view clustering microbiome data by joint symmetric nonnegative matrix factorization with Laplacian regularization

Y Ma, X Hu, T He, X Jiang - 2016 IEEE International …, 2016‏ - ieeexplore.ieee.org
Many datasets existed in the real world are often comprised of different representations or
views which provide complementary information to each other. For example, microbiome …

Fusing heterogeneous modalities for video and image re-ranking

HK Tan, CW Ngo - Proceedings of the 1st ACM International Conference …, 2011‏ - dl.acm.org
Multimedia documents in popular image and video sharing websites such as Flickr and
Youtube are heterogeneous documents with diverse ways of representations and rich user …