Výsledky vyhľadávania - "CURE data clustering algorithm"

Towards U-statistics clustering inference for multiple groups

Autori: Debora Zava Bello Márcio Valk Gabriela Bettella Cybis

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

Predmety: 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 objects for spatial data mining: a comparative study

Autori: Youssef Fakir Rachid Elayachi Btissam MAHI

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

Predmety: 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

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

Autori: Pham Huy Thong Florentín Smarandache Phung The Huan a ďalší

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

Predmety: 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

Optimizing Data Exploration: Unifying Clustering and Association Rule Extraction

Autori: Youssef Fakir

Predmety: 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 novel similarity measure for multiple aspect trajectory clustering

Autori: Iraklis Varlamis Christos Sardianos Vânia Bogorny a ďalší

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

Predmety: 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 súboru: application/pdf

Prístupová 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

Exploiting DBSCAN and Combination Strategy to Prioritize the Test Suite in Regression Testing

Autori: Zikang Zhang Jinfu Chen Yuechao Gu a ďalší

Zdroj: IET Software, Vol 2024 (2024)

Predmety: Prioritization, Computer Networks and Communications, 02 engineering and technology, Testing-Effort Dependent Models, QA76.75-76.765, Cluster analysis, Engineering, Machine learning, 0202 electrical engineering, electronic engineering, information engineering, Test Case Prioritization, Computer software, CURE data clustering algorithm, Fault Localization, Data mining, Software construction, Automated Software Testing Techniques, Sorting, Test suite, Correlation clustering, Regression testing, Computer science, DBSCAN, Management science, Programming language, Overhead (engineering), Algorithm, Operating system, Software Fault Localization, Log Analysis and System Performance Diagnosis, Computer Science, Physical Sciences, Software system, Search-Based Testing, Software Reliability Assessment and Prediction, Test case, Regression analysis, Software

Prístupová URL adresa: https://doaj.org/article/1b82cf6c17564e7cb390e6911bf6605f

A Basis Approach to Surface Clustering

Autori: Adriano Zanin Zambom Qing Wang Ronaldo Dias

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

Predmety: 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

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

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

Autori: Mustafa Tareq Elankovan A Sundararajan Aaron Harwood a ďalší

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

Predmety: 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

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

Clustering validation by distribution hypothesis learning

Autori: Ariel E. Bayá Mónica G. Larese

Zdroj: Statistics and Computing. 34

Predmety: 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

Sentiment Analysis based on Soft Clustering through Dimensionality Reduction Technique

Autori: Saba Akmal Hafiz Muhammad Shahzad Asif

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

Predmety: 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

Prístupová 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

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

Autori: Benjamin Mario Sainz-Tinajero Andres E. Gutierrez-Rodríguez Héctor G. Ceballos a ďalší

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

Predmety: 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

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

Adaptive Landmark-Based Spectral Clustering for Big Datasets

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

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

Predmety: 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

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

Co-Regularized Discriminative Spectral Clustering With Adaptive Similarity Measure in Dual-Kernel Space

Autori: Augustine Monney Yongzhao Zhan Hongjie Jia a ďalší

Zdroj: IEEE Access, Vol 8, Pp 46427-46439 (2020)

Predmety: Artificial intelligence, Support vector machine, Adaptive neighbors, 02 engineering and technology, Pattern recognition (psychology), co-regularize, Engineering, Cluster analysis, Artificial Intelligence, Document Clustering, Spectral clustering, Media Technology, FOS: Mathematics, 0202 electrical engineering, electronic engineering, information engineering, CURE data clustering algorithm, Data mining, Data Clustering Techniques and Algorithms, spectral clustering, Spectral Clustering, Discriminative model, Correlation clustering, Hyperspectral Image Analysis and Classification, Semi-supervised Clustering, Computer science, TK1-9971, similarity measure, multi-kernel, Kernel embedding of distributions, Kernel method, Combinatorics, Physical Sciences, Computer Science, Kernel (algebra), Electrical engineering. Electronics. Nuclear engineering, Computer Vision and Pattern Recognition, Variable kernel density estimation, Face Recognition and Dimensionality Reduction Techniques, Stream Data Clustering, Density-based Clustering, Mathematics

Prístupová URL adresa: https://ieeexplore.ieee.org/ielx7/6287639/8948470/09018059.pdf
https://doaj.org/article/7a691f3788cf49ed8ec3a75741973f8e
https://ieeexplore.ieee.org/document/9018059
https://dblp.uni-trier.de/db/journals/access/access8.html#MonneyZJB20

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

Autori: Mohammed Saad Talib Aslinda Hassan Thamer Alamery a ďalší

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

Predmety: 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

Prístupová 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/

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

Autori: Nicolás Gaitán Jorge Duitama

Zdroj: Gigascience

Predmety: 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

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

A unified view of density-based methods for semi-supervised clustering and classification

Autori: Jadson Castro Gertrudes Arthur Zimek Jörg Sander a ďalší

Prispievatelia: Jadson Castro Gertrudes Arthur Zimek Jörg Sander a ďalší

Zdroj: Data Min Knowl Discov
Castro Gertrudes, J, Zimek, A, Sander, J & Campello, R J G B 2019, ' A unified view of density-based methods for semi-supervised clustering and classification ', Data Mining and Knowledge Discovery, vol. 33, no. 6, pp. 1894-1952 . https://doi.org/10.1007/s10618-019-00651-1

Predmety: Artificial neural network, Artificial intelligence, Data stream clustering, 02 engineering and technology, Pattern recognition (psychology), Article, Graph, Density-based clustering, Clustering Algorithms, Cluster analysis, Theoretical computer science, Artificial Intelligence, Machine learning, 0202 electrical engineering, electronic engineering, information engineering, CURE data clustering algorithm, Adaptation to Concept Drift in Data Streams, Data mining, density-based clustering, Data Clustering Techniques and Algorithms, Semi-supervised classification, Spectral Clustering, Correlation clustering, Semi-supervised Clustering, Computer science, semi-supervised classification, semi-supervised clustering, Computer Science, Physical Sciences, Semi-supervised learning, Computer Vision and Pattern Recognition, Face Recognition and Dimensionality Reduction Techniques, Stream Data Clustering, Density-based Clustering, Supervised learning, Semi-supervised clustering

Prístupová URL adresa: https://link.springer.com/content/pdf/10.1007/s10618-019-00651-1.pdf
https://pubmed.ncbi.nlm.nih.gov/32831623
https://dblp.uni-trier.de/db/journals/datamine/datamine33.html#GertrudesZSC19
https://www.ncbi.nlm.nih.gov/pubmed/32831623
https://link.springer.com/article/10.1007/s10618-019-00651-1
https://dialnet.unirioja.es/servlet/articulo?codigo=7177229
https://repositorio.usp.br/item/002960703
https://europepmc.org/articles/PMC7410108/
https://rdcu.be/bPp7N
https://portal.findresearcher.sdu.dk/da/publications/3a5b5fa1-01b4-4c33-b425-1adce77f0794
https://doi.org/10.1007/s10618-019-00651-1

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

Autori: Haneen A. Abdulwahab Ahmad Noraziah AbdulRahman A. Alsewari a ďalší

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

Predmety: 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

Prístupová 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/

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

Autori: Quang‐Van Doan Toshiyuki Amagasa Thanh-Ha Pham a ďalší

Predmety: 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

Unsupervised clustering of SARS-CoV-2 using deep convolutional autoencoder

Autori: Fayroz F. Sherif Khaled S. Ahmed

Zdroj: J. Eng. Appl. Sci.
Journal of Engineering and Applied Science, Vol 69, Iss 1, Pp 1-22 (2022)

Predmety: 0301 basic medicine, Artificial intelligence, Cluster (spacecraft), FOS: Health sciences, Prediction of Peptide-MHC Binding Affinity, Pattern recognition (psychology), Hierarchical clustering, Computational biology, 0303 health sciences, Wilcoxon signed-rank test, Ecology, Statistics, Life Sciences, Correlation clustering, Autoencoder, Engineering (General). Civil engineering (General), Programming language, 3. Good health, Infectious Diseases, Environmental health, Rank (graph theory), Physical Sciences, Convolutional autoencoder, Medicine, Unsupervised clustering, TA1-2040, Population, Spike protein, Coronavirus Disease 2019 Research, Mann–Whitney U test, 03 medical and health sciences, Cluster analysis, Biochemistry, Genetics and Molecular Biology, Health Sciences, FOS: Mathematics, Lineages, CURE data clustering algorithm, Molecular Biology, Biology, Corona Virus, SARS-CoV-2, Single-linkage clustering, Research, Deep learning, Ecology and Evolution of Viruses in Ecosystems, Computer science, Combinatorics, FOS: Biological sciences, Environmental Science, Mathematics

Prístupová URL adresa: https://doaj.org/article/2a22e124233e43e884ff0513ecf5ee9e

A Co-occurrence Based Approach for Mining Overlapped Co-clusters in Binary Data

Autori: Yuri Santa Rosa Nassar dos Santos Rafael Santiago Raffaele Perego a ďalší

Zdroj: Lecture Notes in Computer Science ISBN: 9783030917012
BRACIS 2021-10th Brazilian Conference on Intelligent Systems, pp. 375–389, Online Conference, 29/11/2021-3/12/2021
info:cnr-pdr/source/autori:Santa Rosa Nassar dos Santos Y.; de Santiago R.; Perego R.; Schaly M.H.; Alvares L.O.; Renso C.; Bogorny V./congresso_nome:BRACIS 2021-10th Brazilian Conference on Intelligent Systems/congresso_luogo:Online Conference/congresso_data:29%2F11%2F2021-3%2F12%2F2021/anno:2021/pagina_da:375/pagina_a:389/intervallo_pagine:375–389

Predmety: Artificial intelligence, Disjoint sets, 02 engineering and technology, Pattern recognition (psychology), 01 natural sciences, Clustering, Trajectories, Co-clustering data mining, Clustering Algorithms, Cluster analysis, Artificial Intelligence, Biochemistry, Genetics and Molecular Biology, Document Clustering, Microarray Data Analysis and Gene Expression Profiling, FOS: Mathematics, 0202 electrical engineering, electronic engineering, information engineering, Binary data, Novelty detection, CURE data clustering algorithm, 0101 mathematics, Molecular Biology, Data mining, Granularity, Data Clustering Techniques and Algorithms, Arithmetic, Fuzzy clustering, Single-linkage clustering, Biclustering, Life Sciences, Novelty, Statistical and Nonlinear Physics, Semi-supervised Clustering, Computer science, FOS: Philosophy, ethics and religion, Philosophy, Operating system, Physics and Astronomy, Combinatorics, Computer Science, Physical Sciences, Statistical Mechanics of Complex Networks, Theology, Binary number, Density-based Clustering, Mathematics

Popis súboru: application/pdf

Prístupová URL adresa: https://zenodo.org/record/5970008/files/BRACIS21_CRC.pdf.pdf
https://link.springer.com/chapter/10.1007/978-3-030-91702-9_25