On the public citation graph

Verification and validation of MapReduce program model for parallel K-means algorithm on Hadoop cluster

https://doi.org/10.1109/icccnt.2013.6726852
0 signed · 43 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-642-10665-1_71openalex-snapshot
Parallel K-Means Clustering Based on MapReduce
inferredcites →https://doi.org/10.1017/cbo9780511804779openalex-snapshot
Bayesian Reasoning and Machine Learning
inferredcites →https://doi.org/10.1109/msst.2010.5496972openalex-snapshot
The Hadoop Distributed File System
inferredcites →https://doi.org/10.1109/wict.2012.6409130openalex-snapshot
Performance analysis of MapReduce programs on Hadoop cluster
inferredcites →https://doi.org/10.1145/1165389.945450openalex-snapshot
The Google file system
inferredcites →https://doi.org/10.1145/1327452.1327492openalex-snapshot
MapReduce
inferredcites →https://doi.org/10.1145/945449.945450openalex-snapshot
The Google file system
inferredcites →https://doi.org/10.2200/s00274ed1v01y201006hlt007openalex-snapshot
Data-Intensive Text Processing with MapReduce
inferredcites →https://doi.org/10.3115/1620950.1620951openalex-snapshot
Data-intensive text processing with MapReduce

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4201182openalex-extracted
Scalable and Robust Big Data Clustering with Adaptive Local Feature Weighting Based on the Map-Reduce and Hadoop
inferred← citeshttps://doi.org/10.1007/978-3-319-25939-0_22openalex-snapshot
Optimized-Memory Map-Reduce Algorithm for Mobile Learning
inferred← citeshttps://doi.org/10.1007/978-3-319-62416-7_15openalex-snapshot
Machine Learning-as-a-Service and Its Application to Medical Informatics
inferred← citeshttps://doi.org/10.1007/s12517-020-05670-7openalex-snapshot
Comparative analysis of unsupervised classification methods for mapping burned forest areas
inferred← citeshttps://doi.org/10.1016/b978-0-443-21475-2.00016-3openalex-snapshot
K-means clustering over distributed environment: A review
inferred← citeshttps://doi.org/10.1016/j.fcij.2018.06.002openalex-snapshot
Partition based clustering of large datasets using MapReduce framework: An analysis of recent themes and directions
inferred← citeshttps://doi.org/10.1016/j.future.2018.09.038openalex-snapshot
Parallel K-Tree: A multicore, multinode solution to extreme clustering
inferred← citeshttps://doi.org/10.1109/calcon.2017.8280774openalex-snapshot
HdK-means: Hadoop based parallel K-means clustering for big data
inferred← citeshttps://doi.org/10.1109/icsai.2014.7009427openalex-snapshot
Clustering massive small data for IOT
inferred← citeshttps://doi.org/10.1109/isit.2018.8437333openalex-snapshot
Coded Distributed Computing with Node Cooperation Substantially Increases Speedup Factors
inferred← citeshttps://doi.org/10.1145/2736277.2741111openalex-snapshot
Parallel Streaming Signature EM-tree
inferred← citeshttps://doi.org/10.1145/3368235.3368845openalex-snapshot
Cloud Instance Selection Using Parallel K-Means and AHP
inferred← citeshttps://doi.org/10.1145/3514221.3517864openalex-snapshot
DataPrism: Exposing Disconnect between Data and Systems
inferred← citeshttps://doi.org/10.14257/ijgdc.2015.8.1.18openalex-snapshot
An Improved K-means Algorithm based on Mapreduce and Grid
inferred← citeshttps://doi.org/10.21203/rs.3.rs-3476807/v1openalex-snapshot
Scalable and robust big data clustering with adaptive local feature weighting based on the Map-Reduce and Hadoop
inferred← citeshttps://doi.org/10.3390/rs9121301openalex-snapshot
Research on the Parallelization of the DBSCAN Clustering Algorithm for Spatial Data Mining Based on the Spark Platform
inferred← citeshttps://doi.org/10.4018/978-1-5225-3445-7.ch009openalex-snapshot
Examining Big Data Management Techniques for Cloud-Based IoT Systems
inferred← citeshttps://doi.org/10.48550/arxiv.2105.06058openalex-snapshot
DataExposer: Exposing Disconnect between Data and Systems
inferred← citeshttps://doi.org/10.5120/15023-3311openalex-snapshot
Asymmetric Key-Value Split Pattern Assumption over MapReduce Behavioral Model
inferred← citeshttps://doi.org/10.5120/16354-5732openalex-snapshot
On The Least Economical MapReduce Sets for Summarization Expressions
inferred← citeshttps://doi.org/10.5120/17160-7216openalex-snapshot
On Randomized Minimal MapReduce Sets for Filtering Expressions
inferred← citeshttps://doi.org/10.5120/17415-8195openalex-snapshot
How Minimal are MapReduce Arrangements for Binning Expressions?
inferred← citeshttps://doi.org/10.5120/17900-8895openalex-snapshot
Shuffling Expressions with MapReduce Arrangements and the Role of Binary Path Symmetry
inferred← citeshttps://doi.org/10.5120/18807-0431openalex-snapshot
How Replicated Join Expressions Equal Map Phase or Reduce Phase in a MapReduce Structure?
inferred← citeshttps://doi.org/10.5120/19347-1055openalex-snapshot
On Composite Join Expressions of Map-side with many Reduce Phase
inferred← citeshttps://doi.org/10.5120/19902-2008openalex-snapshot
On Job Chaining MapReduce Meta Expressions of Mapping and Reducing Entropy Densities
inferred← citeshttps://doi.org/10.5120/20424-2740openalex-snapshot
On Chain Folding Problems of Chain Mapper and Chain Reducer Meta Expressions
inferred← citeshttps://doi.org/10.5120/20804-3501openalex-snapshot
On Job Merging MapReduce Meta Expressions for Multiple Decomposition Mapping and Reducing
inferred← citeshttps://doi.org/10.5120/ijais2016451555openalex-snapshot
Is it Possible to Sequence Continuously Changing Workload Patterns for Periodic Elastic Scaling?
inferred← citeshttps://doi.org/10.5120/ijca2015905403openalex-snapshot
Characterization of Randomized External Source Output Map Reduce Expressions
inferred← citeshttps://doi.org/10.5120/ijca2015906155openalex-snapshot
Does there Exist Pruning Decomposition for MapReduce Expressions Arrangements?
inferred← citeshttps://doi.org/10.5120/ijca2015906680openalex-snapshot
Can one find External Source Input Expressions for which there exist Map Reduce Configurations?
inferred← citeshttps://doi.org/10.5120/ijca2016909294openalex-snapshot
What is a minimum of Unpredictable Workload Pattern over all Elastic Scaling in Cloud Computing?
inferred← citeshttps://doi.org/10.70675/ec499196z0371z4ffaz8c32z7ec091afef2dopenalex-snapshot
The high Dimensionality factor of Coded Caching : Resolving Bottlenecks one Antenna at a time
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.