# Advanced Clustering Algorithms Research

**Type:** Topics  
**Canonical URL:** https://scholariq.org/topics/advanced-clustering-algorithms-research/

## Facts

| Field | Value |
| --- | --- |
| Description | This cluster of papers encompasses advancements in data clustering techniques and algorithms, covering topics such as K-means, cluster validation, high-dimensional data clustering, density-based clustering, semi-supervised clustering, document clustering, fuzzy clustering, evolutionary algorithms for clustering, and stream data clustering. |
| Domain | Physical Sciences |
| Field | Computer Science |
| OpenAlex ID | t10637 |
| Works | 46 |

## Topic papers all

Showing 15 of 46.

- [Co-regularized Multi-view Spectral Clustering](https://scholariq.org/papers/co-regularized-multi-view-spectral-clustering/)
- [A survey of kernel and spectral methods for clustering](https://scholariq.org/papers/a-survey-of-kernel-and-spectral-methods-for-clustering/)
- [A Co-training Approach for Multi-view Spectral Clustering](https://scholariq.org/papers/a-co-training-approach-for-multi-view-spectral-clustering/)
- [Locally Weighted Ensemble Clustering](https://scholariq.org/papers/locally-weighted-ensemble-clustering/)
- [A Comparison of Hierarchical Methods for Clustering Functional Data](https://scholariq.org/papers/a-comparison-of-hierarchical-methods-for-clustering-functional-data/)
- [Multi-View Clustering in Latent Embedding Space](https://scholariq.org/papers/multi-view-clustering-in-latent-embedding-space/)
- [Fast Multi-View Clustering Via Ensembles: Towards Scalability, Superiority, and Simplicity](https://scholariq.org/papers/fast-multi-view-clustering-via-ensembles-towards-scalability-superiority-and/)
- [Adaptive fuzzy-K-means clustering algorithm for image segmentation](https://scholariq.org/papers/adaptive-fuzzy-k-means-clustering-algorithm-for-image-segmentation/)
- [Robust Ensemble Clustering Using Probability Trajectories](https://scholariq.org/papers/robust-ensemble-clustering-using-probability-trajectories/)
- [A comprehensive survey of image segmentation: clustering methods, performance parameters, and benchmark datasets](https://scholariq.org/papers/a-comprehensive-survey-of-image-segmentation-clustering-methods-performance/)
- [Efficient Multi-View Clustering via Unified and Discrete Bipartite Graph Learning](https://scholariq.org/papers/efficient-multi-view-clustering-via-unified-and-discrete-bipartite-graph/)
- [A fuzzy clustering based segmentation system as support to diagnosis in medical imaging](https://scholariq.org/papers/a-fuzzy-clustering-based-segmentation-system-as-support-to-diagnosis-in-medical/)
- [A Novel Clustering Method Using Enhanced Grey Wolf Optimizer and MapReduce](https://scholariq.org/papers/a-novel-clustering-method-using-enhanced-grey-wolf-optimizer-and-mapreduce/)
- [Comparison of Internal Clustering Validation Indices for Prototype-Based Clustering](https://scholariq.org/papers/comparison-of-internal-clustering-validation-indices-for-prototype-based/)
- [A hybridized K-means clustering approach for high dimensional dataset](https://scholariq.org/papers/a-hybridized-k-means-clustering-approach-for-high-dimensional-dataset/)

## Topic primary papers

Showing 15 of 23.

- [A survey of kernel and spectral methods for clustering](https://scholariq.org/papers/a-survey-of-kernel-and-spectral-methods-for-clustering/)
- [A Co-training Approach for Multi-view Spectral Clustering](https://scholariq.org/papers/a-co-training-approach-for-multi-view-spectral-clustering/)
- [Locally Weighted Ensemble Clustering](https://scholariq.org/papers/locally-weighted-ensemble-clustering/)
- [A Comparison of Hierarchical Methods for Clustering Functional Data](https://scholariq.org/papers/a-comparison-of-hierarchical-methods-for-clustering-functional-data/)
- [Fast Multi-View Clustering Via Ensembles: Towards Scalability, Superiority, and Simplicity](https://scholariq.org/papers/fast-multi-view-clustering-via-ensembles-towards-scalability-superiority-and/)
- [Adaptive fuzzy-K-means clustering algorithm for image segmentation](https://scholariq.org/papers/adaptive-fuzzy-k-means-clustering-algorithm-for-image-segmentation/)
- [A fuzzy clustering based segmentation system as support to diagnosis in medical imaging](https://scholariq.org/papers/a-fuzzy-clustering-based-segmentation-system-as-support-to-diagnosis-in-medical/)
- [Comparison of Internal Clustering Validation Indices for Prototype-Based Clustering](https://scholariq.org/papers/comparison-of-internal-clustering-validation-indices-for-prototype-based/)
- [A hybridized K-means clustering approach for high dimensional dataset](https://scholariq.org/papers/a-hybridized-k-means-clustering-approach-for-high-dimensional-dataset/)
- [Soft transition from probabilistic to possibilistic fuzzy clustering](https://scholariq.org/papers/soft-transition-from-probabilistic-to-possibilistic-fuzzy-clustering/)
- [Threshold selection based on cluster analysis](https://scholariq.org/papers/threshold-selection-based-on-cluster-analysis/)
- [Introduction to partitioning-based clustering methods with a robust example](https://scholariq.org/papers/introduction-to-partitioning-based-clustering-methods-with-a-robust-example/)
- [Fuzzy c-means clustering using Jeffreys-divergence based similarity measure](https://scholariq.org/papers/fuzzy-c-means-clustering-using-jeffreys-divergence-based-similarity-measure/)
- [KNN-DBSCAN: Using k-nearest neighbor information for parameter-free density based clustering](https://scholariq.org/papers/knn-dbscan-using-k-nearest-neighbor-information-for-parameter-free-density-based/)
- [Fuzzy K-Means Using Non-Linear S-Distance](https://scholariq.org/papers/fuzzy-k-means-using-non-linear-s-distance/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.