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Categorical Data Clustering: A Bibliometric Analysis and Taxonomy
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Science mapping software tools: Review, analysis, and cooperative study among tools
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Semantically Segmented Clustering Based on Possibilistic and Rough Set Theories
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Error Detecting and Error Correcting Codes
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Improving K-Modes Algorithm Considering Frequencies of Attribute Values in Mode
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Clustering Approach Using Belief Function Theory
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Clustering Transactional Data
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Applications of Data Mining in Computer Security
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A Systematic Review on Supervised and Unsupervised Machine Learning Algorithms for Data Science
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Clustering Based on Sequential Multi-Objective Games
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A k-Means-Like Algorithm for Clustering Categorical Data Using an Information Theoretic-Based Dissimilarity Measure
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Categorical Data Visualization and Clustering Using Subjective Factors
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A New Initialization Method for Clustering Categorical Data
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Transactions on Rough Sets VIII
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Comparison of Similarity Measures for Categorical Data in Hierarchical Clustering
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Rough subspace-based clustering ensemble for categorical data
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Automatic clustering algorithms: a systematic review and bibliometric analysis of relevant literature
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Multi-instance clustering with applications to multi-instance prediction
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Some bibliometric procedures for analyzing and evaluating research fields
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k-PbC: an improved cluster center initialization for categorical data clustering
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Attribute weights-based clustering centres algorithm for initialising K-modes clustering
inferredcites →https://doi.org/10.1007/s10618-011-0221-2openalex-snapshot
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Cluster validity functions for categorical data: a solution-space perspective
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Citation-based clustering of publications using CitNetExplorer and VOSviewer
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Link-based approach to study scientific software usage: the case of VOSviewer
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A tutorial on spectral clustering
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inferredcites →https://doi.org/10.1007/s13042-019-01012-6openalex-snapshot
Fuzzy rough clustering for categorical data
inferredcites →https://doi.org/10.1007/s13042-021-01293-wopenalex-snapshot
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Nature-inspired metaheuristic techniques for automatic clustering: a survey and performance study
inferredcites →https://doi.org/10.1016/0003-2670(93)80130-dopenalex-snapshot
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inferredcites →https://doi.org/10.1016/0167-8655(95)00075-ropenalex-snapshot
A conceptual version of the K-means algorithm
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inferredcites →https://doi.org/10.1016/j.asoc.2015.01.031openalex-snapshot
Non-dominated sorting genetic algorithm using fuzzy membership chromosome for categorical data clustering
inferredcites →https://doi.org/10.1016/j.asoc.2017.04.019openalex-snapshot
k -mw-modes: An algorithm for clustering categorical matrix-object data
inferredcites →https://doi.org/10.1016/j.asoc.2018.11.028openalex-snapshot
Partition-and-merge based fuzzy genetic clustering algorithm for categorical data
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New fuzzy C-means clustering method based on feature-weight and cluster-weight learning
inferredcites →https://doi.org/10.1016/j.asoc.2020.106981openalex-snapshot
Two graph-regularized fuzzy subspace clustering methods
inferredcites →https://doi.org/10.1016/j.chaos.2021.111494openalex-snapshot
FKMAWCW: Categorical fuzzy k-modes clustering with automated attribute-weight and cluster-weight learning
inferredcites →https://doi.org/10.1016/j.cie.2018.04.050openalex-snapshot
Application of metaheuristic based fuzzy K-modes algorithm to supplier clustering
inferredcites →https://doi.org/10.1016/j.compeleceng.2018.04.023openalex-snapshot
A fast and effective partitional clustering algorithm for large categorical datasets using a k -means based approach
inferredcites →https://doi.org/10.1016/j.datak.2007.03.016openalex-snapshot
A k-mean clustering algorithm for mixed numeric and categorical data
inferredcites →https://doi.org/10.1016/j.datak.2007.05.005openalex-snapshot
MMR: An algorithm for clustering categorical data using Rough Set Theory
inferredcites →https://doi.org/10.1016/j.engappai.2016.01.026openalex-snapshot
A modified Fuzzy k-Partition based on indiscernibility relation for categorical data clustering
inferredcites →https://doi.org/10.1016/j.engappai.2022.105795openalex-snapshot
An efficient entropy based dissimilarity measure to cluster categorical data
inferredcites →https://doi.org/10.1016/j.eswa.2007.11.045openalex-snapshot
A genetic fuzzy k -Modes algorithm for clustering categorical data
inferredcites →https://doi.org/10.1016/j.eswa.2009.01.060openalex-snapshot
A new initialization method for categorical data clustering
inferredcites →https://doi.org/10.1016/j.eswa.2011.01.074openalex-snapshot
A fuzzy c-means-type algorithm for clustering of data with mixed numeric and categorical attributes employing a probabilistic dissimilarity functional
inferredcites →https://doi.org/10.1016/j.eswa.2013.07.002openalex-snapshot
Cluster center initialization algorithm for K-modes clustering
inferredcites →https://doi.org/10.1016/j.eswa.2017.12.013openalex-snapshot
Many-objective fuzzy centroids clustering algorithm for categorical data
inferredcites →https://doi.org/10.1016/j.eswa.2020.113555openalex-snapshot
Uncertainty mode selection in categorical clustering using the rough set theory
inferredcites →https://doi.org/10.1016/j.eswa.2023.121860openalex-snapshot
Density peak clustering algorithms: A review on the decade 2014–2023
inferredcites →https://doi.org/10.1016/j.fss.2007.08.012openalex-snapshot
A fuzzy k-partitions model for categorical data and its comparison to the GoM model
inferredcites →https://doi.org/10.1016/j.fss.2012.06.005openalex-snapshot
A novel fuzzy clustering algorithm with between-cluster information for categorical data
inferredcites →https://doi.org/10.1016/j.fss.2018.02.007openalex-snapshot
Integrated Rough Fuzzy Clustering for Categorical data Analysis
inferredcites →https://doi.org/10.1016/j.ijinfomgt.2017.04.007openalex-snapshot
Co-citation and cluster analyses of extant literature on social networks
inferredcites →https://doi.org/10.1016/j.inffus.2004.03.001openalex-snapshot
A cluster ensemble method for clustering categorical data
inferredcites →https://doi.org/10.1016/j.inffus.2006.05.006openalex-snapshot
k-ANMI: A mutual information based clustering algorithm for categorical data
inferredcites →https://doi.org/10.1016/j.ins.2008.06.008openalex-snapshot
Clustering algorithm for intuitionistic fuzzy sets
inferredcites →https://doi.org/10.1016/j.ins.2015.11.005openalex-snapshot
Initialization of K-modes clustering using outlier detection techniques
inferredcites →https://doi.org/10.1016/j.ins.2020.12.051openalex-snapshot
Metaheuristic-based possibilistic fuzzy k-modes algorithms for categorical data clustering
inferredcites →https://doi.org/10.1016/j.ins.2022.11.139openalex-snapshot
K-means clustering algorithms: A comprehensive review, variants analysis, and advances in the era of big data
inferredcites →https://doi.org/10.1016/j.is.2014.06.008openalex-snapshot
Rough set approach for clustering categorical data using information-theoretic dependency measure
inferredcites →https://doi.org/10.1016/j.jbusres.2021.04.070openalex-snapshot
How to conduct a bibliometric analysis: An overview and guidelines
inferredcites →https://doi.org/10.1016/j.joi.2016.10.006openalex-snapshot
Constructing bibliometric networks: A comparison between full and fractional counting
inferredcites →https://doi.org/10.1016/j.joi.2017.08.007openalex-snapshot
bibliometrix : An R-tool for comprehensive science mapping analysis
inferredcites →https://doi.org/10.1016/j.knosys.2009.11.001openalex-snapshot
G-ANMI: A mutual information based genetic clustering algorithm for categorical data
inferredcites →https://doi.org/10.1016/j.knosys.2009.12.003openalex-snapshot
A rough set approach for selecting clustering attribute
inferredcites →https://doi.org/10.1016/j.knosys.2011.07.011openalex-snapshot
A dissimilarity measure for the k-Modes clustering algorithm
inferredcites →https://doi.org/10.1016/j.knosys.2012.06.001openalex-snapshot
A novel soft set approach in selecting clustering attribute
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A spectral clustering algorithm based on intuitionistic fuzzy information
inferredcites →https://doi.org/10.1016/j.knosys.2014.03.013openalex-snapshot
MGR: An information theory based hierarchical divisive clustering algorithm for categorical data
inferredcites →https://doi.org/10.1016/j.knosys.2014.04.008openalex-snapshot
Hierarchical clustering algorithm for categorical data using a probabilistic rough set model
inferredcites →https://doi.org/10.1016/j.knosys.2015.01.008openalex-snapshot
Ensemble based rough fuzzy clustering for categorical data
inferredcites →https://doi.org/10.1016/j.knosys.2018.12.007openalex-snapshot
Density-sensitive fuzzy kernel maximum entropy clustering algorithm
inferredcites →https://doi.org/10.1016/j.neucom.2012.11.009openalex-snapshot
A weighting k-modes algorithm for subspace clustering of categorical data
inferredcites →https://doi.org/10.1016/j.neucom.2012.12.074openalex-snapshot
Robust local feature weighting hard c-means clustering algorithm
inferredcites →https://doi.org/10.1016/j.neucom.2013.11.024openalex-snapshot
The k-modes type clustering plus between-cluster information for categorical data
inferredcites →https://doi.org/10.1016/j.neucom.2015.03.037openalex-snapshot
Categorical fuzzy k-modes clustering with automated feature weight learning
inferredcites →https://doi.org/10.1016/j.neucom.2015.08.018openalex-snapshot
Applying subclustering and Lp distance in Weighted K-Means with distributed centroids
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A multi-act sequential game-based multi-objective clustering approach for categorical data
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Learning category distance metric for data clustering
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Genetic intuitionistic weighted fuzzy k-modes algorithm for categorical data
inferredcites →https://doi.org/10.1016/j.neucom.2019.02.043openalex-snapshot
Hierarchical division clustering framework for categorical data
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An LSH-based k -representatives clustering method for large categorical data
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A kernel-based intuitionistic weight fuzzy k-modes algorithm using coupled chained P system combines DNA genetic rules for categorical data
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An optimization algorithm for clustering using weighted dissimilarity measures
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A novel attribute weighting algorithm for clustering high-dimensional categorical data
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Soft subspace clustering of categorical data with probabilistic distance
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Optimal mathematical programming and variable neighborhood search for k-modes categorical data clustering
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A categorical data clustering framework on graph representation
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Fuzzy clustering of categorical data using fuzzy centroids
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QROCK: A quick version of the ROCK algorithm for clustering of categorical data
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A method to compute distance between two categorical values of same attribute in unsupervised learning for categorical data set
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A Modified Short and Fukunaga Metric based on the attribute independence assumption
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A novel density peaks clustering algorithm for mixed data
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A comprehensive survey of traditional, merge-split and evolutionary approaches proposed for determination of cluster number
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Clustering categorical data sets using tabu search techniques
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Rock: A robust clustering algorithm for categorical attributes
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Extensions to the k-Means Algorithm for Clustering Large Data Sets with Categorical Values
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Clustering by phenotype and genome-wide association study in autism
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Clustering Categorical Data via Ensembling Dissimilarity Matrices
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Clustering in the field of social sciences: that is your choice
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A Fast Parallel K-Modes Algorithm for Clustering Nucleotide Sequences to Predict Translation Initiation Sites
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Exploratory Latent Structure Analysis Using Both Identifiable and Unidentifiable Models
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A fuzzy k-modes algorithm for clustering categorical data
inferredcites →https://doi.org/10.1109/access.2019.2893063openalex-snapshot
Brain Image Segmentation Based on FCM Clustering Algorithm and Rough Set
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Automatic Fuzzy Clustering Using Non-Dominated Sorting Particle Swarm Optimization Algorithm for Categorical Data
inferredcites →https://doi.org/10.1109/access.2019.2935089openalex-snapshot
Heterogeneous Graph Based Similarity Measure for Categorical Data Unsupervised Learning
inferredcites →https://doi.org/10.1109/access.2022.3162690openalex-snapshot
A Novel Cluster Prediction Approach Based on Locality-Sensitive Hashing for Fuzzy Clustering of Categorical Data
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IK-BKM: An incremental clustering approach based on intra-cluster distance
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Kernel-Based k-Representatives Algorithm for Fuzzy Clustering of Categorical Data
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The k-modes method using possibility and rough set theories
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A survey of distance/similarity measures for categorical data
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The DRk-M for Clustering Categorical Datasets With Uncertainty
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Fuzzy clustering for categorical multivariate data
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SDR: An algorithm for clustering categorical data using rough set theory
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A New Distance Metric Exploiting Heterogeneous Interattribute Relationship for Ordinal-and-Nominal-Attribute Data Clustering
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Multiobjective Genetic Algorithm-Based Fuzzy Clustering of Categorical Attributes
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A possibilistic fuzzy c-means clustering algorithm
inferredcites →https://doi.org/10.1109/tfuzz.2022.3189831openalex-snapshot
Graph Enhanced Fuzzy Clustering for Categorical Data Using a Bayesian Dissimilarity Measure
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An Entropy Weighting k-Means Algorithm for Subspace Clustering of High-Dimensional Sparse Data
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Top-Down Parameter-Free Clustering of High-Dimensional Categorical Data
inferredcites →https://doi.org/10.1109/tkde.2010.268openalex-snapshot
A Link-Based Cluster Ensemble Approach for Categorical Data Clustering
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Information-Theoretic Outlier Detection for Large-Scale Categorical Data
inferredcites →https://doi.org/10.1109/tkde.2018.2808532openalex-snapshot
Unsupervised Coupled Metric Similarity for Non-IID Categorical Data
inferredcites →https://doi.org/10.1109/tkde.2018.2848902openalex-snapshot
CURE: Flexible Categorical Data Representation by Hierarchical Coupling Learning
inferredcites →https://doi.org/10.1109/tnnls.2014.2325872openalex-snapshot
Coupled Attribute Similarity Learning on Categorical Data
inferredcites →https://doi.org/10.1109/tnnls.2015.2436432openalex-snapshot
A New Distance Metric for Unsupervised Learning of Categorical Data
inferredcites →https://doi.org/10.1109/tnnls.2015.2451151openalex-snapshot
Space Structure and Clustering of Categorical Data
inferredcites →https://doi.org/10.1109/tnnls.2017.2728138openalex-snapshot
Subspace Clustering of Categorical and Numerical Data With an Unknown Number of Clusters
inferredcites →https://doi.org/10.1109/tnnls.2017.2770167openalex-snapshot
An Algorithm for Clustering Categorical Data With Set-Valued Features
inferredcites →https://doi.org/10.1109/tnnls.2019.2899381openalex-snapshot
A Unified Entropy-Based Distance Metric for Ordinal-and-Nominal-Attribute Data Clustering
inferredcites →https://doi.org/10.1109/tnnls.2019.2911118openalex-snapshot
From Whole to Part: Reference-Based Representation for Clustering Categorical Data
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Automated variable weighting in k-means type clustering
inferredcites →https://doi.org/10.1109/tpami.2007.53openalex-snapshot
On the Impact of Dissimilarity Measure in k-Modes Clustering Algorithm
inferredcites →https://doi.org/10.1109/tpami.2012.228openalex-snapshot
The impact of cluster representatives on the convergence of the K-modes type clustering
inferredcites →https://doi.org/10.1109/tpami.2020.3010953openalex-snapshot
Unsupervised Heterogeneous Coupling Learning for Categorical Representation
inferredcites →https://doi.org/10.1109/tpami.2021.3056510openalex-snapshot
Learnable Weighting of Intra-attribute Distances for Categorical Data Clustering with Nominal and Ordinal Attributes
inferredcites →https://doi.org/10.1126/science.1127647openalex-snapshot
Reducing the Dimensionality of Data with Neural Networks
inferredcites →https://doi.org/10.1136/bmj.n71openalex-snapshot
The PRISMA 2020 statement: an updated guideline for reporting systematic reviews
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Similarity Measures for Categorical Data: A Comparative Evaluation
inferredcites →https://doi.org/10.1142/s0219622019300064openalex-snapshot
Clustering Categorical Data: A Survey
inferredcites →https://doi.org/10.1142/s021972000900400xopenalex-snapshot
CLUSTERING OF GENE EXPRESSION DATA AND END-POINT MEASUREMENTS BY SIMULATED ANNEALING
inferredcites →https://doi.org/10.1145/1007730.1007731openalex-snapshot
Subspace clustering for high dimensional data
inferredcites →https://doi.org/10.1145/1015330.1015404openalex-snapshot
Entropy-based criterion in categorical clustering
inferredcites →https://doi.org/10.1145/2063576.2063715openalex-snapshot
Coupled nominal similarity in unsupervised learning
inferredcites →https://doi.org/10.1155/2015/238237openalex-snapshot
Intuitionistic Fuzzy Possibilistic C Means Clustering Algorithms
inferredcites →https://doi.org/10.1155/2017/8986360openalex-snapshot
Clustering Categorical Data Using Community Detection Techniques
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A DNA Genetic Algorithm Inspired by Biological Membrane Structure
inferredcites →https://doi.org/10.1177/0095798420930932openalex-snapshot
Latent Class Analysis: A Guide to Best Practice
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Research on face feature extraction based on K-mean algorithm
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Model-Based Clustering, Discriminant Analysis, and Density Estimation
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An Algorithm for Selecting Clustering Attribute using Significance of Attributes
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Face Extraction from Image based on K-Means Clustering Algorithms
inferredcites →https://doi.org/10.14569/ijacsa.2021.0120950openalex-snapshot
Customer Segmentation and Profiling for Life Insurance using K-Modes Clustering and Decision Tree Classifier
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