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Iterative big data clustering algorithms: a review
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/3-540-46502-2_13openalex-snapshot
A Data-Clustering Algorithm on Distributed Memory Multiprocessors
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Introduction to algorithms
inferredcites →https://doi.org/10.1007/978-3-319-09156-3_49openalex-snapshot
Big Data Clustering: A Review
inferredcites →https://doi.org/10.1007/978-3-642-10665-1_71openalex-snapshot
Parallel K-Means Clustering Based on MapReduce
inferredcites →https://doi.org/10.1007/978-3-642-25661-5_13openalex-snapshot
A Parallel Cop-Kmeans Clustering Algorithm Based on MapReduce Framework
inferredcites →https://doi.org/10.1007/978-3-642-39640-3_16openalex-snapshot
Parallel Two-Phase K-Means
inferredcites →https://doi.org/10.1007/bf02547521openalex-snapshot
Über Die Praktische Auflösung von Integralgleichungen mit Anwendungen auf Randwertaufgaben
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A survey of large-scale analytical query processing in MapReduce
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Top 10 algorithms in data mining
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PEGASUS: mining peta-scale graphs
inferredcites →https://doi.org/10.1007/s10723-012-9204-9openalex-snapshot
iMapReduce: A Distributed Computing Framework for Iterative Computation
inferredcites →https://doi.org/10.1007/s11227-014-1174-1openalex-snapshot
A parallel clustering method combined information bottleneck theory and centroid-based clustering
inferredcites →https://doi.org/10.1007/s11227-014-1225-7openalex-snapshot
Optimized big data K-means clustering using MapReduce
inferredcites →https://doi.org/10.1016/j.future.2011.05.025openalex-snapshot
Adapting scientific computing problems to clouds using MapReduce
inferredcites →https://doi.org/10.1016/j.is.2013.11.002openalex-snapshot
DBCURE-MR: An efficient density-based clustering algorithm for large data using MapReduce
inferredcites →https://doi.org/10.1016/j.jpdc.2014.08.003openalex-snapshot
Big Data computing and clouds: Trends and future directions
inferredcites →https://doi.org/10.1080/03772063.2014.988760openalex-snapshot
Multidimensional Canopy Clustering on Iterative MapReduce Framework Using Elefig Tool
inferredcites →https://doi.org/10.1103/physreve.76.036106openalex-snapshot
Near linear time algorithm to detect community structures in large-scale networks
inferredcites →https://doi.org/10.1109/aina.2013.47openalex-snapshot
PSCAN: A Parallel Structural Clustering Algorithm for Big Networks in MapReduce
inferredcites →https://doi.org/10.1109/iccis.2011.223openalex-snapshot
Research on Clustering Algorithm and Its Parallelization Strategy
inferredcites →https://doi.org/10.1109/icdm.2006.123openalex-snapshot
P3C: A Robust Projected Clustering Algorithm
inferredcites →https://doi.org/10.1109/icdm.2008.142openalex-snapshot
DisCo: Distributed Co-clustering with Map-Reduce: A Case Study towards Petabyte-Scale End-to-End Mining
inferredcites →https://doi.org/10.1109/icdm.2013.76openalex-snapshot
Co-ClusterD: A Distributed Framework for Data Co-Clustering with Sequential Updates
inferredcites →https://doi.org/10.1109/icpads.2011.83openalex-snapshot
MR-DBSCAN: An Efficient Parallel Density-Based Clustering Algorithm Using MapReduce
inferredcites →https://doi.org/10.1109/ipdps.2011.260openalex-snapshot
iMapReduce: A Distributed Computing Framework for Iterative Computation
inferredcites →https://doi.org/10.1109/nabic.2012.6402247openalex-snapshot
Parallel particle swarm optimization clustering algorithm based on MapReduce methodology
inferredcites →https://doi.org/10.1109/pdcat.2009.46openalex-snapshot
An Efficient Hierarchical Clustering Method for Large Datasets with Map-Reduce
inferredcites →https://doi.org/10.1109/tpami.2010.88openalex-snapshot
Parallel Spectral Clustering in Distributed Systems
inferredcites →https://doi.org/10.1109/tpds.2012.272openalex-snapshot
PrIter: A Distributed Framework for Prioritizing Iterative Computations
inferredcites →https://doi.org/10.1137/1.9781611973440.49openalex-snapshot
Embed and Conquer: Scalable Embeddings for Kernel k-Means on MapReduce
inferredcites →https://doi.org/10.1145/1007730.1007731openalex-snapshot
Subspace clustering for high dimensional data
inferredcites →https://doi.org/10.1145/1559845.1559865openalex-snapshot
A comparison of approaches to large-scale data analysis
inferredcites →https://doi.org/10.1145/1807128.1807138openalex-snapshot
Stateful bulk processing for incremental analytics
inferredcites →https://doi.org/10.1145/2020408.2020516openalex-snapshot
Clustering very large multi-dimensional datasets with MapReduce
inferredcites →https://doi.org/10.1145/3749740.3749753openalex-snapshot
A Bridging Model for Parallel Computation
inferredcites →https://doi.org/10.1145/380995.381010openalex-snapshot
Distributed data clustering can be efficient and exact
inferredcites →https://doi.org/10.1145/502512.502550openalex-snapshot
Co-clustering documents and words using bipartite spectral graph partitioning
inferredcites →https://doi.org/10.1186/1471-2105-15-37openalex-snapshot
A network-assisted co-clustering algorithm to discover cancer subtypes based on gene expression
inferredcites →https://doi.org/10.1243/0954406041319509openalex-snapshot
An Incremental K-means algorithm
inferredcites →https://doi.org/10.4156/jdcta.vol4.issue3.9openalex-snapshot
A New Agglomerative Hierarchical Clustering Algorithm Implementation based on the Map Reduce Framework
inferredcites →https://doi.org/10.48550/arxiv.physics/0004057openalex-snapshot
The information bottleneck method
inferredcites →https://doi.org/10.5441/002/edbt.2014.06openalex-snapshot
Projected Clustering for Huge Data Sets in MapReduce
inferredcites →https://doi.org/10.5555/1283383.1283494openalex-snapshot
k-means++: the advantages of careful seeding
inferredcites →https://doi.org/10.5555/1855741.1855742openalex-snapshot
DryadLINQ: a system for general-purpose distributed data-parallel computing using a high-level language
inferredcites →https://doi.org/10.5860/choice.28-4558openalex-snapshot
Finding groups in data: an introduction to cluster analysis
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Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Big Data Clustering Using MapReduce Framework: A Review
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Big Data Clustering Techniques: Recent Advances and Survey
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Density Peaks Clustering Based on Improved RNA Genetic Algorithm
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Overview of Scalable Partitional Methods for Big Data Clustering
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A Fine‐Grained Distribution Approach for ETL Processes in Big Data Environments
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Parallel K-Tree: A multicore, multinode solution to extreme clustering
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Identifying manufacturing operational conditions by physics-based feature extraction and ensemble clustering
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Performance enhancement of a dynamic K-means algorithm through a parallel adaptive strategy on multicore CPUs
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A stratified sampling based clustering algorithm for large-scale data
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Utility-efficient differentially private K-means clustering based on cluster merging
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Electricity consumption behaviour analysis based on adaptive weighted‐feature K‐means‐AP clustering
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A New Cluster Validity Index Based on the Adjustment of Within-Cluster Distance
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Towards a Hierarchical Exascale Framework for Iterative Parallel Data Analysis Algorithms
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Collaborative Accelerators for Streamlining MapReduce on Scale-up Machines With Incremental Data Aggregation
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A Comprehensive Survey on Cloud Data Mining (CDM) Frameworks and Algorithms
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Density-based Algorithms for Big Data Clustering Using MapReduce Framework
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