Data Clustering

Data clustering aims to partition data points into groups (clusters) based on similarity, facilitating data analysis and interpretation. Current research emphasizes developing robust and efficient algorithms for diverse data types, including high-dimensional, categorical, and graph data, with a focus on improving scalability and incorporating fairness considerations. Prominent approaches involve density-based methods, Bayesian techniques, and deep learning models, often incorporating graph structures or self-supervised learning. These advancements are impacting various fields, from satellite communication optimization and medical image analysis to financial modeling and news prioritization.

Papers

August 28, 2023

Some issues in robust clustering
Christian Hennig
Data Clustering Gaussian Mixture Model Proper Issue Labeling Global Outlier Robust Clustering

August 18, 2023

Eigenvalue-based Incremental Spectral Clustering
Mieczysław A. Kłopotek, Bartłmiej Starosta, Sławomir T. Wierzchoń
Data Clustering Spectral Clustering Smallest Eigenvalue Incremental Clustering

August 9, 2023

Multi-modal Multi-view Clustering based on Non-negative Matrix Factorization
Yasser Khalafaoui, Nistor Grozavu, Basarab Matei, Laurent-Walter Goix
Multi View Matrix Factorization Data Clustering Non Negative Matrix Factorization Negative Matrix Factorization

August 1, 2023

Explainable Graph Spectral Clustering of Text Documents
Bartłomiej Starosta, Mieczysław A. Kłopotek, Sławomir T. Wierzchoń
Data Clustering Spectral Clustering Clustering Result Explainable Clustering Text Document

July 17, 2023

Snapshot Spectral Clustering -- a costless approach to deep clustering ensembles generation
Adam Piróg, Halina Kwaśnicka
Deep Learning Deep Neural Network Ensemble Learning Data Clustering Deep Ensemble Spectral Clustering Cost Effective Approach

July 14, 2023

Visualizing Overlapping Biclusterings and Boolean Matrix Factorizations
Thibault Marette, Pauli Miettinen, Stefan Neumann
Matrix Factorization Data Clustering Cluster Structure Bipartite Graph Bi Cluster

July 10, 2023

Fast dynamic time warping and clustering in C++
Volkan Kumtepeli, Rebecca Perriment, David A. Howey
Time Series Data Data Clustering Mixed Integer Dynamic Time Warping Time Series Datasets C++ Implementation

July 8, 2023

Feature selection simultaneously preserving both class and cluster structures
Suchismita Das, Nikhil R. Pal
Feature Selection Hyperspectral Image Data Clustering True Class

July 6, 2023

DPM: Clustering Sensitive Data through Separation
Yara Schütt, Johannes Liebenow, Tanya Braun, Marcel Gehrke, Florian Thaeter, Esfandiar Mohammadi
Data Clustering Sensitive Data Separation Performance Private Clustering

July 3, 2023

Spatio-Temporal Surrogates for Interaction of a Jet with High Explosives: Part II -- Clustering Extremely High-Dimensional Grid-Based Data
Chandrika Kamath, Juliette S. Franzman
Data Clustering Interaction Generation Random Projection Energetic Material Iterative Clustering Multiple Jet

July 2, 2023

Large Language Models Enable Few-Shot Clustering
Vijay Viswanathan, Kiril Gashteovski, Carolin Lawrence, Tongshuang Wu, Graham Neubig
Large Language Model Data Clustering Semi Supervised Clustering Semi Supervised Few Shot

June 24, 2023

A clustering and graph deep learning-based framework for COVID-19 drug repurposing
Chaarvi Bansal, Rohitash Chandra, Vinti Agarwal, P. R. Deepa
Data Clustering Heterogeneous Clinical Drug Target Drug Repurposing Drug Labeling

June 22, 2023

An Interactive Interface for Novel Class Discovery in Tabular Data
Colin Troisemaine, Joachim Flocon-Cholet, Stéphane Gosselin, Alexandre Reiffers-Masson, Sandrine Vaton, Vincent Lemaire
Tabular Data Data Clustering Novel Class Discovery Interactive Interface

June 16, 2023

Correlation Clustering of Bird Sounds
David Stein, Bjoern Andres
Data Clustering Different Cluster Correlation Clustering Animal Sound Sound Classification Bird Sound

June 12, 2023

A Computational Theory and Semi-Supervised Algorithm for Clustering
Nassir Mohammad
Data Clustering Clustering Method Semi Supervised Clustering Efficient Clustering

May 30, 2023

Deep Clustering with Incomplete Noisy Pairwise Annotations: A Geometric Regularization Approach
Tri Nguyen, Shahana Ibrahim, Xiao Fu
Data Clustering Deep Clustering Noisy Annotation Geometric Regularization Constrained Clustering Deep Multiple Clustering

May 26, 2023

Clustering Method for Time-Series Images Using Quantum-Inspired Computing Technology
Tomoki Inoue, Koyo Kubota, Tsubasa Ikami, Yasuhiro Egami, Hiroki Nagai, Takahiro Kashikawa, Koichi Kimura, Yu Matsuda
Time Series Practical Method Time Series Data Data Clustering Clustering Result Scalable Quantum

May 24, 2023

Classic machine learning methods
Johann Faouzi, Olivier Colliot
NCD Method Unsupervised Learning Data Clustering Nearest Neighbor Logistic Regression Vector Machine

May 17, 2023

Improving Link Prediction in Social Networks Using Local and Global Features: A Clustering-based Approach
Safiye Ghasemi, Amin Zarei
Link Prediction Data Clustering Social Network Global Feature Social Network Analysis Node Similarity Clustering Based Approach

May 11, 2023

Entropy-Aware Similarity for Balanced Clustering: A Case Study with Melanoma Detection
Seok Bin Son, Soohyun Park, Joongheon Kim
Case Study Data Clustering Imbalanced Data Melanoma Detection Feature Similarity