[PDF] Top 20 Big Data Analysis Using Fuzzy Clustering Algorithms Implemented on Spark Framework

Big Data Analysis Using Fuzzy Clustering Algorithms Implemented on Spark Framework

... of data gets collected everyday due to the increasing involvement of humans in the digital ...of data, and Walmart’s databases contain more than ...of data. Such huge amount of data containing ... See full document

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Efficient Big Data Analysis using Fuzzy Based Clustering Law with Apache Spark Proposals

... Evolving Big Data" such as as new information and upgrades are continually arriving, the aftereffects of information mining applications get to be distinctly stale and out of date over the long ... See full document

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QUALITY AND ACCURACY OF CLUSTERING ALGORITHMS ON BIG DATA SETS USING HADOOP

... maintained, analysis of performance and retried ...a Big Data solution of problems to solve and some of these components can be replaced with other technologies that better complement a user's needs ... See full document

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Some Improvements of Fuzzy Clustering Algorithms Using Picture Fuzzy Sets and Applications For Geographic Data Clustering

... some fuzzy clustering methods by the mean of more generalized fuzzy ...distributed fuzzy clustering method for big data using picture fuzzy sets; design a ... See full document

7

Big Data Clustering Using Heuristic Data Intensive Computing and Self Organizing Maps

... Traditional data clustering algorithms are having pitfalls while discovering efficient ...the data base size increases dynamically and the dramatic changes in the use of data, will ... See full document

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DATA STORING AND RETRIEVAL METHOD IN BIG DATA USING FUZZY BASED SCALABLE CLUSTERING ALGORITHMS

... the framework of fuzzy rule mining is completed in an isolated stage, though certain approaches proceeds into versioning the knowledge machines then they regularly eliminate single feature by a period in a ... See full document

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A Hybrid Genetic Fuzzy k modes and Artificial Bee Colony Approach for Clustering YouTube Data

... performance analysis, the proposed hybrid genetic fuzzy k-modes and artificial bee colony clustering algorithm implemented on real time streaming YouTube ...the clustering results of ... See full document

5

Partitional Based Clustering Algorithms on Big Data Using Apache Spark

... Apache Spark, a framework similar to the Von Neumann ...of data. Data captured at high velocity and from variety of different sources known as Big ...Such big data can be ... See full document

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A Comparative Study of Brain Tumour Detection Using K- Harmonic Means, Expectation Maximization and Hierarchical Clustering Algorithms

... In this paper, modified image segmentation techniques were applied on MRI scan images in order to detect brain tumours. Also in this paper, a modified Probabilistic Neural Network (PNN) model that is based on learning ... See full document

8

Clustering methods for Big data analysis

... based clustering method optimizes the fit between the given data and some (predefined) mathematical ...the data were generated by a model or by a mixture of underlying probability distributions and ... See full document

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Comparative Data Analysis based on Fuzzy Clustering Algorithm and FGA

... improved clustering algorithm based on FGA. Clustering techniques play a key role in many ...the clustering techniques. Clustering is a potential technique in many data mining ...Result ... See full document

5

An Efficient Clustering Process using Optimized C Means Algorithm in Social Media Data

... of data mining ...optimized fuzzy means cluster distance algorithm for grouping related ...proposed framework is twofold for overcome existing ...time clustering of social ... See full document

5

GeoMatch:Efficient Large Scale Map Matching on Apache Spark

... benchmarks using the data sets in Table ...performed using source code obtained from the frameworks’ respective GIT ...only framework to consistently time out, requiring more than 180 minutes ... See full document

8

Semi Supervised Clustering Ensemble Approaches Over Multiple Datasets

... ordering data of comparable wide research, likewise in application, the objective space with dynamic learning algorithm, to streamline the point name ...neighbour data hubs these two methodologies builds ... See full document

5

Big Data Analysis on WSN for Risk Analysis on Different Data

... term big data sets so large or complex data sets where the traditional data processing applications are ...of data in the world was generated in last two years. Hence Big ... See full document

6

MRMR BA: A HYBRID GENE SELECTION ALGORITHM FOR CANCER CLASSIFICATION

... to Big Data is volume since it brings a need for scalable power and storage, as well as a distributed technique to ...of data archived and captured over the years. That data can be in the form ... See full document

12

A New Approach For Mining Fuzzified Dataset Using Eclat And Apriori Algorithm

... Geospatial data (GD) is information concerning events, objects or phenomena located on the earth's ...Geospatial data incorporates information on location (generally earth- coordinates), data on ... See full document

6

Towards HPC and Big Data Convergence in a Component Based Approach

... Contributions • Performance analysis of Big Data Tools • Time series data visualization • Parallel streaming algorithms • HPC integration to big data • Twister2 Big data toolkit.. • Unif[r] ... See full document

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Insurance Fraud Detection Using Big Data Analytics

... hybrid framework. 2) Predictive Analytics for Big Data: Predictive analytics include the use of text analytics and sentiment analysis to look at big data for fraud ...easily. ... See full document

13

Learning Spark Lightning Fast Big Data Analysis pdf

... The type of counting shown here becomes especially handy when there are multiple values to keep track of, or when the same value needs to increase at multiple places in the parallel program (for example, you might be ... See full document

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