Výsledky vyhledávání - CURE data clustering algorithm

Clustering objects for spatial data mining: a comparative study

Autoři: Youssef Fakir Rachid Elayachi Btissam MAHI

Zdroj: Journal of Big Data Research. 1:1-11

Témata: FOS: Computer and information sciences, Artificial intelligence, Trajectory Data Mining and Analysis, 7. Clean energy, Clustering Algorithms, Cluster analysis, Artificial Intelligence, Data Mining Techniques and Applications, Document Clustering, 11. Sustainability, FOS: Mathematics, CURE data clustering algorithm, Data mining, Medoid, Data Clustering Techniques and Algorithms, 4. Education, Statistics, Spatial analysis, Correlation clustering, 15. Life on land, Semi-supervised Clustering, Computer science, Computer Science, Physical Sciences, Signal Processing, Object (grammar), Stream Data Clustering, Density-based Clustering, Mathematics, Information Systems, Spatial database

Landslide susceptibility mapping using O-CURE and PAM clustering algorithms

Autoři: Deborah Simon Mwakapesa Xiaoji Lan Yaser Ahangari Nanehkaran a další

Zdroj: Frontiers in Environmental Science, Vol 11 (2023)

Témata: landslide susceptibility mapping, clustering algorithm, CURE, cluster quality, uncertain data, O-CURE, Environmental sciences, GE1-350

Popis souboru: electronic resource

Relation: https://www.frontiersin.org/articles/10.3389/fenvs.2023.1140834/full; https://doaj.org/toc/2296-665X

Přístupová URL adresa: https://doaj.org/article/e4ba28b3a7824d59abe401c31f87f302

Picture-Neutrosophic Trusted Safe Semi-Supervised Fuzzy Clustering for Noisy Data

Autoři: Pham Huy Thong Florentín Smarandache Phung The Huan a další

Zdroj: Computer Systems Science and Engineering. 46:1981-1997

Témata: Artificial intelligence, Data stream clustering, Image Analysis, 02 engineering and technology, Pattern recognition (psychology), Engineering, Cluster analysis, Image Feature Retrieval and Recognition Techniques, Machine learning, Media Technology, 0202 electrical engineering, electronic engineering, information engineering, 14. Life underwater, CURE data clustering algorithm, Canopy clustering algorithm, Data mining, Geography, Spectral Clustering, Fuzzy clustering, 4. Education, Change Detection, Correlation clustering, Hyperspectral Image Analysis and Classification, Computer science, Fuzzy logic, Spectral Unmixing, Outlier, Physical Sciences, Computer Science, 8. Economic growth, Clustering high-dimensional data, Consensus clustering, Computer Vision and Pattern Recognition, Benchmark (surveying), Face Recognition and Dimensionality Reduction Techniques, Feature Matching, Geodesy

An Enhanced Version of Black Hole Algorithm via Levy Flight for Optimization and Data Clustering Problems

Autoři: Haneen A. Abdulwahab Ahmad Noraziah AbdulRahman A. Alsewari a další

Zdroj: IEEE Access, Vol 7, Pp 142085-142096 (2019)

Témata: Optimization, Economics and Econometrics, Data stream clustering, Robustness (evolution), Social Sciences, metaheuristic, Local optimum, 02 engineering and technology, Econophysics: Complexity in Financial Markets, Biochemistry, Gene, Computational Complexity and Algorithmic Information Theory, Cluster analysis, Artificial Intelligence, Hashing, computational intelligence, Machine learning, black hole, 0202 electrical engineering, electronic engineering, information engineering, CURE data clustering algorithm, Optimization problem, Canopy clustering algorithm, Data mining, Computability, Geography, Text Compression and Indexing Algorithms, Correlation clustering, Computer science, TK1-9971, Algorithm, Economics, Econometrics and Finance, Chemistry, data clustering, Computational Theory and Mathematics, levy flight, Computer Science, Physical Sciences, Electrical engineering. Electronics. Nuclear engineering, Benchmark (surveying), Algorithms, Geodesy

Přístupová URL adresa: https://ieeexplore.ieee.org/ielx7/6287639/8600701/08809737.pdf
https://doaj.org/article/2a3f5b0e368f4c47ae7b3e853fc55c92
https://dblp.uni-trier.de/db/journals/access/access7.html#AbdulwahabNAS19
https://ieeexplore.ieee.org/document/8809737
http://umpir.ump.edu.my/id/eprint/27559/

Optimizing Data Exploration: Unifying Clustering and Association Rule Extraction

Autoři: Youssef Fakir

Témata: FOS: Computer and information sciences, Rough Sets Theory and Applications, Artificial intelligence, Decision Analysis, MEDLINE, FOS: Political science, Data extraction, FOS: Law, Clustering Algorithms, Fuzzy Clustering, Cluster analysis, Context (archaeology), Knowledge extraction, Artificial Intelligence, Data Mining Techniques and Applications, Document Clustering, Machine learning, CURE data clustering algorithm, Data mining, Political science, Data Clustering Techniques and Algorithms, Association rule learning, Geography, Correlation clustering, Computer science, Computational Theory and Mathematics, Archaeology, Computer Science, Physical Sciences, Relevance (law), Consensus clustering, Stream Data Clustering, Law, Information Systems

A Systematic Review of Density Grid-Based Clustering for Data Streams

Autoři: Mustafa Tareq Elankovan A Sundararajan Aaron Harwood a další

Zdroj: IEEE Access, Vol 10, Pp 579-596 (2022)

Témata: Data stream clustering, Geometry, 02 engineering and technology, Clustering of Time Series Data and Algorithms, Clustering, Cluster analysis, Artificial Intelligence, Data Streams, Document Clustering, Machine learning, FOS: Mathematics, 0202 electrical engineering, electronic engineering, information engineering, CURE data clustering algorithm, Grid, data stream, Adaptation to Concept Drift in Data Streams, Data mining, density-based clustering, Data Clustering Techniques and Algorithms, grid-based clustering, Correlation clustering, Data stream mining, data stream clustering, Computer science, TK1-9971, Computer Science, Physical Sciences, Signal Processing, Electrical engineering. Electronics. Nuclear engineering, Stream Data Clustering, Density-based Clustering, Mathematics

Přístupová URL adresa: https://doaj.org/article/8de2244d65d14a5cabde1c667c334bc2

A Center-Based Stable Evolving Clustering Algorithm With Grid Partitioning and Extended Mobility Features for VANETs

Autoři: Mohammed Saad Talib Aslinda Hassan Thamer Alamery a další

Zdroj: IEEE Access, Vol 8, Pp 169908-169921 (2020)

Témata: Artificial intelligence, Social Sciences, Geometry, Transportation, Vehicular Ad Hoc Networks, 02 engineering and technology, center-based clustering, Intelligent Transportation Systems, FOS: Economics and business, Internet of Vehicles, Engineering, Cluster analysis, Market segmentation, Machine learning, 11. Sustainability, FOS: Electrical engineering, electronic engineering, information engineering, FOS: Mathematics, 0202 electrical engineering, electronic engineering, information engineering, Business, Electrical and Electronic Engineering, Grid, CURE data clustering algorithm, Stability (learning theory), Data mining, Marketing, Vehicular ad hoc networks, VANETs clustering, grid based-clustering, VANET Security, Correlation clustering, Traffic Flow Prediction and Forecasting, Building and Construction, Computer science, TK1-9971, evolving clustering, Physical Sciences, Vehicular Ad Hoc Networks and Communications, Transportation Modes, Electrical engineering. Electronics. Nuclear engineering, Consistency (knowledge bases), Mathematics, Understanding Human Mobility Patterns

Přístupová URL adresa: https://ieeexplore.ieee.org/ielx7/6287639/8948470/09181523.pdf
https://doaj.org/article/14d8128f797b49859a1f093a66b1d671
https://dblp.uni-trier.de/db/journals/access/access8.html#TalibHAAMIA20
https://ieeexplore.ieee.org/document/9181523/

Towards U-statistics clustering inference for multiple groups

Autoři: Debora Zava Bello Márcio Valk Gabriela Bettella Cybis

Zdroj: Journal of Statistical Computation and Simulation. 94:204-222

Témata: Statistics and Probability, Artificial intelligence, Regularization and Variable Selection Methods, Variational Inference, Clustering, Statistical hypothesis testing, Cluster analysis, Inference, Artificial Intelligence, Biochemistry, Genetics and Molecular Biology, Microarray Data Analysis and Gene Expression Profiling, Machine learning, FOS: Mathematics, CURE data clustering algorithm, Molecular Biology, Data mining, Statistic, Fuzzy clustering, Statistics, Life Sciences, Computer science, Test statistic, Outlier, Computer Science, Physical Sciences, Clustering high-dimensional data, High-Dimensional Data, Model-Based Clustering with Mixture Models, Mathematics, Statistical inference

Clustering Gene Expression Data Through Modified Agglomerative M-CURE Hierarchical Algorithm.

Autoři: Kavitha, E. Tamilarasan, R. Poonguzhali, N. a další

Zdroj: Computer Systems Science & Engineering. 2022, Vol. 41 Issue 3, p1027-1041. 15p.

Témata: Gene expression, K-means clustering, Dimension reduction (Statistics), Biological networks, Metabolites

A graph clustering algorithm for detection and genotyping of structural variants from long reads

Autoři: Nicolás Gaitán Jorge Duitama

Zdroj: Gigascience

Témata: 0301 basic medicine, Genotyping, Artificial intelligence, Nanopore sequencing, Genotype, sequence variation, Genome Evolution and Polyploidy in Plants, 0206 medical engineering, Plant Science, 02 engineering and technology, Gene, Agricultural and Biological Sciences, Computational biology, 03 medical and health sciences, Cluster analysis, Biochemistry, Genetics and Molecular Biology, Phenotype Analysis, Exome Sequencing, Technical Note, Genetics, Cluster Analysis, DNA sequencing, Indel, CURE data clustering algorithm, RNA Sequencing Data Analysis, Data mining, Molecular Biology, Biology, Single-nucleotide polymorphism, Genome, Correlation clustering, Life Sciences, Bayes Theorem, Phylogenetic Analysis, Genomics, Standards and Guidelines for Genetic Variant Interpretation, Structural Variation, DBSCAN, Computer science, Genomic Rearrangements and Copy Number Variations, Algorithm, Variant Databases, FOS: Biological sciences, sequence alignment, Structural variation, Algorithms

Přístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/38206589

Novel clustering framework using k-means (S k-means) for mining spatiotemporal structured climate data

Autoři: Quang‐Van Doan Toshiyuki Amagasa Thanh-Ha Pham a další

Témata: Atmospheric Science, Artificial intelligence, FOS: Political science, Climate Change and Variability Research, FOS: Law, Quantum mechanics, 01 natural sciences, Satellite-Based Precipitation Estimation and Validation, Cluster analysis, Image (mathematics), Entropy (arrow of time), Similarity (geometry), CURE data clustering algorithm, Data mining, Political science, 0105 earth and related environmental sciences, Global and Planetary Change, Fuzzy clustering, Physics, Politics, Numerical Weather Prediction Models, Computer science, Silhouette, Earth and Planetary Sciences, 13. Climate action, Physical Sciences, Environmental Science, Consensus clustering, Representation (politics), Law, Climate Modeling

PERFORMANCE EVALUATION OF SELECTED DISTANCE-BASED AND DISTRIBUTION-BASED CLUSTERING ALGORITHMS

Autoři: Adeleke Raheem Ajiboye

Zdroj: International Journal of Software Engineering and Computer Systems. 4:38-48

Témata: Artificial intelligence, Data stream clustering, Cluster (spacecraft), 02 engineering and technology, Pattern recognition (psychology), Clustering Algorithms, Cluster analysis, Artificial Intelligence, Document Clustering, Shape Matching and Object Recognition, 0202 electrical engineering, electronic engineering, information engineering, Image Compression Techniques and Standards, CURE data clustering algorithm, Canopy clustering algorithm, Data mining, Data Clustering Techniques and Algorithms, Single-linkage clustering, Correlation clustering, Semi-supervised Clustering, Computer science, Programming language, Algorithm, Computer Science, Physical Sciences, Computer Vision and Pattern Recognition, Determining the number of clusters in a data set, Stream Data Clustering, Density-based Clustering

Přístupová URL adresa: https://journal.ump.edu.my/ijsecs/article/download/194/24
https://journal.ump.edu.my/ijsecs/article/view/194

A novel similarity measure for multiple aspect trajectory clustering

Autoři: Iraklis Varlamis Christos Sardianos Vânia Bogorny a další

Zdroj: SAC 21-36th Annual ACM Symposium on Applied Computing, pp. 551–558, Online Conference, 22-26/03/2021
info:cnr-pdr/source/autori:Varlamis I.; Sardianos C.; Bogorny V.; Alvares L.O.; Carvalho J.T.; Renso C.; Perego R.; Violos J./congresso_nome:SAC 21-36th Annual ACM Symposium on Applied Computing/congresso_luogo:Online Conference/congresso_data:22-26%2F03%2F2021/anno:2021/pagina_da:551/pagina_a:558/intervallo_pagine:551–558
SAC
Proceedings of the 36th Annual ACM Symposium on Applied Computing

Témata: Artificial intelligence, Similarity Search, Semantic Trajectories, FOS: Political science, Trajectory Data Mining and Analysis, Social Sciences, Transportation, FOS: Law, 02 engineering and technology, Clustering of Time Series Data and Algorithms, Pattern recognition (psychology), Clustering, Hierarchical clustering, Trajectories, Cluster analysis, Similarity measure, Image (mathematics), 0202 electrical engineering, electronic engineering, information engineering, Similarity (geometry), CURE data clustering algorithm, Data mining, Political science, Fuzzy clustering, Politics, Measure (data warehouse), Computer science, Semantic trajectories, Semantic similarity, Trajectory Data Mining, Signal Processing, Computer Science, Physical Sciences, Similarity Measures, Consensus clustering, Representation (politics), Law, Understanding Human Mobility Patterns

Popis souboru: application/pdf

Přístupová URL adresa: https://dl.acm.org/doi/pdf/10.1145/3412841.3441935
https://dblp.uni-trier.de/db/conf/sac/sac2021.html#VarlamisSBACR0V21
https://doi.org/10.1145/3412841.3441935
https://hdl.handle.net/20.500.14243/399396
https://doi.org/10.1145/3412841.3441935

A Basis Approach to Surface Clustering

Autoři: Adriano Zanin Zambom Qing Wang Ronaldo Dias

Zdroj: Statistics, Optimization & Information Computing. 10:339-351

Témata: FOS: Computer and information sciences, Artificial intelligence, Data stream clustering, Trajectory Data Mining and Analysis, Computational Mechanics, Geometry, Basis (linear algebra), Mathematical analysis, 01 natural sciences, Methodology (stat.ME), Clustering Algorithms, Engineering, Cluster analysis, Artificial Intelligence, Document Clustering, Spectral clustering, FOS: Mathematics, Analysis of Three-Dimensional Shape Structures, CURE data clustering algorithm, 0101 mathematics, Data mining, Statistics - Methodology, Data Clustering Techniques and Algorithms, Geography, Correlation clustering, Semi-supervised Clustering, Computer science, Algorithm, Dimension (graph theory), Combinatorics, Signal Processing, Computer Science, Physical Sciences, Basis function, Benchmark (surveying), Stream Data Clustering, Density-based Clustering, Consistency (knowledge bases), Mathematics, Geodesy

Přístupová URL adresa: http://arxiv.org/abs/2102.01769

F1-ECAC: Enhanced Evolutionary Clustering Using an Ensemble of Supervised Classifiers

Autoři: Benjamin Mario Sainz-Tinajero Andres E. Gutierrez-Rodríguez Héctor G. Ceballos a další

Zdroj: IEEE Access, Vol 9, Pp 134192-134207 (2021)

Témata: Cluster Validation, Artificial intelligence, Data stream clustering, 02 engineering and technology, Pattern recognition (psychology), Unsupervised learning, classifier ensembles, evolutionary clustering, Clustering Algorithms, Constrained clustering, Cluster analysis, Artificial Intelligence, Document Clustering, Machine learning, FOS: Mathematics, 0202 electrical engineering, electronic engineering, information engineering, Swarm Intelligence Optimization Algorithms, CURE data clustering algorithm, Canopy clustering algorithm, Data mining, Data Clustering Techniques and Algorithms, Fuzzy clustering, Correlation clustering, Semi-supervised Clustering, Computer science, TK1-9971, Application of Genetic Programming in Machine Learning, Computer Science, Physical Sciences, Electrical engineering. Electronics. Nuclear engineering, optimization, Density-based Clustering, Mathematics, clustering

Přístupová URL adresa: https://ieeexplore.ieee.org/ielx7/6287639/6514899/09551203.pdf
https://doaj.org/article/13a0f1c0f9214d4e88d36043f4dc3bb0

Adaptive Landmark-Based Spectral Clustering for Big Datasets

Autoři: Ahmed R. Abas Mohamed G. Mahdy Tarek M. Mahmoud

Zdroj: IEEE Access, Vol 9, Pp 88291-88300 (2021)

Témata: Artificial neural network, Artificial intelligence, parallel processing, Data stream clustering, landmark-based spectral clustering, big datasets, MNIST database, 02 engineering and technology, Pattern recognition (psychology), Clustering Algorithms, Big data, Landmark, Cluster analysis, Artificial Intelligence, Spectral clustering, 0202 electrical engineering, electronic engineering, information engineering, CURE data clustering algorithm, Theory and Applications of Extreme Learning Machines, Canopy clustering algorithm, Data mining, Data Clustering Techniques and Algorithms, Spectral Clustering, Single-linkage clustering, Correlation clustering, Semi-supervised Clustering, Computer science, TK1-9971, Computer Science, Physical Sciences, Clustering high-dimensional data, Electrical engineering. Electronics. Nuclear engineering, Computer Vision and Pattern Recognition, Adaptive competitive learning neural network, Face Recognition and Dimensionality Reduction Techniques, Stream Data Clustering, Density-based Clustering, clustering

Přístupová URL adresa: https://ieeexplore.ieee.org/ielx7/6287639/6514899/09450802.pdf
https://doaj.org/article/2dbf81e482bc4e8aa590d9371882ac31

An Heterogeneous Population-Based Genetic Algorithm for Data Clustering

Autoři: Cherif Bouras Mohamed Tahar Kimour Amina Bedboudi

Zdroj: Indonesian Journal of Electrical Engineering and Informatics (IJEEI). 5

Témata: FOS: Computer and information sciences, Artificial intelligence, Population, 02 engineering and technology, Clustering Algorithms, Cluster analysis, Sociology, Artificial Intelligence, Data Mining Techniques and Applications, Document Clustering, Machine learning, 0502 economics and business, 0202 electrical engineering, electronic engineering, information engineering, Swarm Intelligence Optimization Algorithms, CURE data clustering algorithm, Canopy clustering algorithm, Adaptation to Concept Drift in Data Streams, Data mining, Demography, Data Clustering Techniques and Algorithms, 05 social sciences, Correlation clustering, Semi-supervised Clustering, Computer science, FOS: Sociology, Algorithm, Genetic algorithm, Computer Science, Physical Sciences, Crossover, Determining the number of clusters in a data set, Stream Data Clustering, Density-based Clustering, Information Systems

Přístupová URL adresa: http://section.iaesonline.com/index.php/IJEEI/article/download/299/200
http://section.iaesonline.com/index.php/IJEEI/article/download/299/200
http://section.iaesonline.com/index.php/IJEEI/article/view/299

Sentiment Analysis based on Soft Clustering through Dimensionality Reduction Technique

Autoři: Saba Akmal Hafiz Muhammad Shahzad Asif

Zdroj: Mehran University Research Journal of Engineering and Technology, Vol 40, Iss 3, Pp 630-644 (2021)

Témata: FOS: Computer and information sciences, Technology, Artificial intelligence, Data stream clustering, Science, Principal component analysis, Set (abstract data type), 02 engineering and technology, Pattern recognition (psychology), 7. Clean energy, Detection and Prevention of Phishing Attacks, Behavioral Analysis, Cluster analysis, Artificial Intelligence, Aspect-based Sentiment Analysis, Multi-label Text Classification in Machine Learning, Sentiment Analysis, 0202 electrical engineering, electronic engineering, information engineering, Feature Selection, CURE data clustering algorithm, Canopy clustering algorithm, Data mining, Fuzzy clustering, Correlation clustering, Engineering (General). Civil engineering (General), Computer science, Dimensionality reduction, Programming language, Sentiment Analysis and Opinion Mining, 13. Climate action, Emotion Recognition, Computer Science, Physical Sciences, Clustering high-dimensional data, TA1-2040, Information Systems

Přístupová URL adresa: https://publications.muet.edu.pk/index.php/muetrj/article/download/2186/537
https://doaj.org/article/0eb7dff3db2e41589d550427df081bf0
https://ui.adsabs.harvard.edu/abs/2021MURJE..40..630A/abstract

Clustering validation by distribution hypothesis learning

Autoři: Ariel E. Bayá Mónica G. Larese

Zdroj: Statistics and Computing. 34

Témata: Artificial neural network, Cluster Validation, Artificial intelligence, Overfitting, Pattern recognition (psychology), Anomaly Detection in High-Dimensional Data, Clustering Algorithms, Cluster analysis, Artificial Intelligence, Machine learning, CURE data clustering algorithm, Stability (learning theory), Data mining, Data Clustering Techniques and Algorithms, Spectral Clustering, Fuzzy clustering, 4. Education, Correlation clustering, 15. Life on land, 16. Peace & justice, Semi-supervised Clustering, Computer science, Computer Science, Physical Sciences, Consensus clustering, Computer Vision and Pattern Recognition, Classifier (UML), Face Recognition and Dimensionality Reduction Techniques, Density-based Clustering

Simrec: a similarity measure recommendation system for mixed data clustering algorithms.

Autoři: Diop, Abdoulaye El-Malki, Nabil Chevalier, Max a další

Zdroj: Journal of Big Data; 2/22/2025, Vol. 12 Issue 1, p1-37, 37p

Témata: CLUSTERING algorithms, MACHINE learning, ARTIFICIAL intelligence, RECOMMENDER systems, HIERARCHICAL clustering (Cluster analysis)