Concept

Medoid

OpenAlex ID: C63085389

A simple and fast algorithm for K-medoids clustering

2008 · Hae-Sang Park, Chi-Hyuck Jun · Expert Systems with Applications · 2,186

Defining clusters from a hierarchical cluster tree: the Dynamic Tree Cut package for R

2007 · Peter Langfelder, Bin Zhang, et al. · Bioinformatics · 1,885

Cluster-wise assessment of cluster stability

2006 · Christian Hennig · Computational Statistics & Data Analysis · 1,028

Quick Shift and Kernel Methods for Mode Seeking

2008 · Andrea Vedaldi, Stefano Soatto · Lecture notes in computer science · 949

Partitioning Around Medoids (Program PAM)

1990 · Leonard Kaufman, Peter J. Rousseeuw · Wiley series in probability and statistics · 850

A Survey of Evolutionary Algorithms for Clustering

2009 · E.R. Hruschka, R.J.G.B. Campello, et al. · IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews) · 761

Mixture of experts: a literature survey

2012 · Saeed Masoudnia, Reza Ebrahimpour · Artificial Intelligence Review · 597

Analysis of K-Means and K-Medoids Algorithm For Big Data

2016 · Preeti Arora, Deepali, et al. · Procedia Computer Science · 568

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Faster k-Medoids Clustering: Improving the PAM, CLARA, and CLARANS Algorithms

2019 · Erich Schubert, Peter J. Rousseeuw · Lecture notes in computer science · 369

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WeightedCluster Library Manual: A practical guide to creating typologies of trajectories in the social sciences with R

2013 · Studer, Matthias · Archive ouverte UNIGE (University of Geneva) · 330

Seasonal Composite Landsat TM/ETM+ Images Using the Medoid (a Multi-Dimensional Median)

2013 · Neil Flood · Remote Sensing · 313

A new partitioning around medoids algorithm

2003 · Mark Van der Laan, Katherine Pollard, et al. · Journal of Statistical Computation and Simulation · 304

U-BIOPRED clinical adult asthma clusters linked to a subset of sputum omics

2016 · Diane Lefaudeux, Bertrand De Meulder, et al. · Journal of Allergy and Clinical Immunology · 301

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Fast and eager k -medoids clustering: O ( k ) runtime improvement of the PAM, CLARA, and CLARANS algorithms

2021 · Erich Schubert, Peter J. Rousseeuw · Information Systems · 292

Opinion mining from online hotel reviews – A text summarization approach

2016 · Ya-Han Hu, Yen-Liang Chen, et al. · Information Processing & Management · 290

Clustering methods to find representative periods for the optimization of energy systems: An initial framework and comparison

2019 · Holger Teichgraeber, Adam R. Brandt · Applied Energy · 285

Delineating urban functional areas with building-level social media data: A dynamic time warping (DTW) distance based k-medoids method

2016 · Yimin Chen, Xiaoping Liu, et al. · Landscape and Urban Planning · 274

Computational Complexity between K-Means and K-Medoids Clustering Algorithms for Normal and Uniform Distributions of Data Points

2010 · Velmurugan · Journal of Computer Science · 258

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Scaling and time warping in time series querying

2007 · Ada Wai-Chee Fu, Eamonn Keogh, et al. · The VLDB Journal · 227

Selection of typical demand days for CHP optimization

2011 · Fernando Domínguez-Muñoz, José M. Cejudo-López, et al. · Energy and Buildings · 217

Unsupervised Clustering Approach for Network Anomaly Detection

2012 · Iwan Syarif, Adam Prugel-Bennett, et al. · Communications in computer and information science · 207

A fuzzy relative of the k-medoids algorithm with application to web document and snippet clustering

1999 · R. Krishnapuram, A. Joshi, et al. · IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) · 199

Hierarchical Taxonomy-Aware and Attentional Graph Capsule RCNNs for Large-Scale Multi-Label Text Classification

2019 · Hao Peng, Jianxin Li, et al. · IEEE Transactions on Knowledge and Data Engineering · 179

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Mode-seeking by Medoidshifts

2007 · Yaser Ajmal Sheikh, Erum Arif Khan, et al. · IEEE/CVF International Conference on Computer Vision (ICCV) · 168

The k-Nearest Neighbour Join: Turbo Charging the KDD Process

2004 · Christian B�hm, Florian Krebs · Knowledge and Information Systems · 149

Works count: 2,373

Citation count: 33,790