[PDF] Top 20 A Parallel Clustering Method Study Based on MapReduce
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A Parallel Clustering Method Study Based on MapReduce
... Abstract: Clustering is considered as the most important task in data ...of clustering is to determine the intrinsic grouping in a set of unlabeled ...earth-quake study, and World Wide Web and so on. ... See full document
8
Study on Parallel SVM Based on MapReduce
... mining, parallel SVM are studied and some parallel SVM methods are ...currently parallel SVM methods are based on classical MPI ...problems. MapReduce is an efficient distribution ... See full document
7
Parallel Particle Swarm Optimization Clustering Algorithm based on MapReduce Methodology
... particular, clustering of large scale data has received considerable attention in the last few years and many application areas such as bioinformatics and social networking are in urgent need of scalable ...of ... See full document
8
Parallel Voronoi Diagram Construction Method With Mapreduce
... a parallel construction method with MapReduce is ...This method uses the incremental insertion algorithm to construct the Delaunay triangulation mesh rapidly, and then transforms it to the ... See full document
7
Parallel Optimal Grid Clustering algorithm exploration on MapReduce Framework
... 36 While conventional data warehouse analytics tend to be based on periodic - daily, weekly or monthly-loads and updates of data, big data is processed and analyzed in real- or near-real- time. This is important ... See full document
5
Parallel Implementation of Fuzzy Clustering Algorithm Based on MapReduce Computing Model of Hadoop –A Detailed Survey
... Data mining is also known as knowledge discovery in databases. Data mining extracts mysterious probable valuable information or pattern from large, incomplete, noisy, blur, random data. With the hasty development of ... See full document
5
Parallel swarm intelligence strategies for large-scale clustering based on MapReduce with application to epigenetics of aging
... data clustering; it is a primary method to extract the first layer of information from unlabeled data ...data clustering techniques ...quality clustering. In this paper, a parallel and ... See full document
44
Big data clustering with varied density based on MapReduce
... prevalent method of density-based clustering algorithms, the most important feature of which is the ability to detect arbitrary shapes and varied clusters and noise ...for clustering big data ... See full document
16
Parallel Tree Reduction on MapReduce
... on MapReduce, e.g., [27, 28, 29]. The common idea is to iterate MapReduce rounds (jobs) in which the Map is applied to each vertex to produce partial results from its internal state, the partial results are ... See full document
10
MapReduce for Parallel Reinforcement Learning
... using MapReduce, a popular parallel computing ...present parallel versions of several dynamic programming algorithms, including policy evaluation, policy iteration, and off-policy ...design ... See full document
12
DATA CLUSTERING USING MAPREDUCE
... Data clustering is a common computing task that often involves large data sets for which MapReduce can be an attractive means to a ...case study of clustering Netflix movie data using K-means, ... See full document
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Large-Scale Data Sets Clustering Based on MapReduce and Hadoop
... Abstract MapReduce is a simplified programming model of distributed parallel computing．It is an important technology of Google，and is commonly used for data—intensive distributed parallel ... See full document
8
Clustering categorical data based on the relational analysis approach and MapReduce
... a MapReduce- based implementation of the well-known DBSCAN ...proposed parallel method consists of four ...set based on pairs lists collected from the previous ... See full document
16
A skewness-based clustering method
... results based on some evaluation index. In fact, point prototype clustering algorithms often converge to local optimal solutions, if the initialization is not suit- able for the data at ...recursive ... See full document
163
Research on HCKM Algorithm Based on Parallel Clustering
... the method, using serial processing data to obtain information, apparently hasn’t met our ...datasets. Based on Hadoop platform, this paper puts forward a kind of Canopy-Kmedoids parallel algorithm, ... See full document
5
A Survey on Parallel Method for Rough Set using MapReduce Technique for Data Mining
... unprecedented rate. Variety: Different types of data and data sources. Variety is about managing the complexity of multiple data types, including structured, semi-structured and unstructured data. Organizations need to ... See full document
5
MapReduce based Classification for Microarray data using Parallel Genetic Algorithm
... Inorder to uncover thousands of genes Microarray produces high throughput is used. Only few gene expression data out of thousands of data is used for disease predication and also for disease classification in medical ... See full document
7
A MapReduce-based Adjoint method for preventing brain disease
... statistical study, we would like to answer the following questions: do these variables really impact the Alz- heimer’s disease risk? Is there a relationship between the variables? If so, define this rela- ... See full document
17
Scalable Embeddings for Kernel Clustering on MapReduce
... data. Clustering is one of the powerful tools that data scientists can employ to discover natural groupings in ...network based on their friendship networks, clustering customers according to their ... See full document
75
Efficient clustering of massive data with MapReduce
... replicated among all computational nodes and the data pages are distributed on the available computers. Zhou et al. [ZZC + 00] proposed an approach for shared-memory multi- processor systems in 2000. As PDBSCAN, the ... See full document
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