[PDF] Top 20 Trabajo de Investigacion GRUPO AJE
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Map/Reduce Affinity Propagation Clustering Algorithm
... Abstract—The Affinity Propagation (AP) is a clustering algorithm that does not require pre-set K cluster ...to Map/Reduce Affinity Propagation (MRAP) implemented in ... See full document
74
Comparatively Analysis on K Means++ and Mini Batch K Means Clustering Algorithm in Cloud Computing with Map Reduce
... k-means clustering algorithm [29] is the alternative and modified version of the k-means ...this algorithm uses mini-batches to reduce the computation time and cost in large datasets not using ... See full document
282
ENHANCEMENT OF MAP REDUCE FRAMEWORK USING CLUSTERING TECHNIQUES
... The Map reduce is a programming model for handling and processing the huge datasets using map and reduce tasks in parallel ...of map reduce many number of activities have been ... See full document
5
An Online Based Approach for Health Care Using Clustering Algorithm with Map Reduce For Scalable Data
... In this paper, local-recoding anonymization for big data in cloud has been investigated from the perspectives of capability of defending proximity privacy breaches, scalability and time-efficiency. We have proposed a ... See full document
14
Optimization of Traveling Salesman Problem based on Adaptive Affinity Propagation and Ant Colony Algorithms
... new algorithm is proposed, that uses Adaptive Affinity Propagation clustering to optimize the performance of Ant Colony Algorithm, to solve ...Adaptive Affinity ... See full document
63
An Efficient Kernel Affinity Propagation Method for Document Clustering
... Porter algorithm is used for stemming process. Porter algorithm is a linear algorithm; exactly it has five phases applying rules within each ... See full document
126
Clustering students' open ended questionnaire answers
... of clustering short texts automat- ...of clustering free-formed questionnaire ...HITS algorithm. The main result is that, for English data, affinity propagation performed well despite ... See full document
125
Content Clustering Analysis Using Modern Map Reduce Model
... In the accessible system, the datasets undergo frequent item sets mining with Apriority Algorithm. But considering the large datasets, apriority attempts to fail the reliability and efficiency. To overcome this we ... See full document
35
Research and Optimization of Data Classification using K means Clustering and Affinity Propagation Technique
... K-means clustering algorithm works best when the centroids are chosen initially and the centroids chosen are close to the optimal ...The algorithm iterates through every data item in each ...the ... See full document
9
TRAINING AND DEVELOPMENT OFARTIFICIAL NEURAL NETWORK MODELS: SINGLE LAYER FEEDFORWARD AND MULTI LAYER FEEDFORWARD NEURAL NETWORK
... of Affinity Propagation clustering algorithm combined RFM model aims to determine the pattern of the data contained in customer transaction and customer identification with customer ... See full document
15
Enhancing Map-Reduce Mechanism for Big Data with Density-Based Clustering
... IDBSCAN algorithm is capable of adding points in the bulk to existing set of ...this algorithm data points are added to the first cluster using DBSCAN algorithm and after that new clusters are merged ... See full document
12
OPTIMIZATION OF MAP REDUCE APPLICATIONS USING PARTITION AND AGGREGATION IN BIG DATA APPLICATION
... called Map Reduce was proposed whose fundamental idea is to simplify the parallel processing using a distributed computing platform that offers only two ...further reduce network traffic within a ... See full document
47
Map Reduce Text Clustering Using Vector Space Model
... of clustering text documents is Vector space model , in which tf-idf is used for k-means algorithm with supportive similarity ...executing map reduce k-means algorithm on both single ... See full document
58
Efficient Clustering on Big Data Map Reduce Using DBScan
... local clustering stage. In the local clustering stage, RDD- DBSCAN performs local clustering for each partition using the traditional DBSCAN ...local clustering, RDD-DBSCAN will load all the ... See full document
47
Map Reduce Design for Data Clustering
... processing. Clustering is one such approach in data mining used to analyse large volume of data generated by real world ...applications. Clustering is a process of partitioning data in such a way that data ... See full document
11
Fingerprint indoor positioning algorithm based on affinity propagation clustering
... In the experiments, we only focus on the situations that the damping factor is in the range of [0.5, 0.9] because only the damping factor falling into this range can guar- antee that the affinity clustering ... See full document
10
Big Data Analytics: Map Reduce Function using BIRCH Clustering Algorithm
... Every algorithm has their significance, and we use them on the nature of the data, but on the basis of this research, we concluded that Map-Reduce function with k-means clustering ... See full document
105
Overview of Fuzzy Clustering Algorithm on Hadoop Map Reduce Computing
... fuzzy algorithm on MapReduce computing environment of ...k-means algorithm has ...of clustering and data mining gradually becomes a hot concept of ...parallel clustering algorithm tend ... See full document
5
Firefly Algorithm based Map Reduce for Large Scale Data Clustering
... create clustering methodology suitable for huge volume of data, Zhao et ...of clustering in addition to get better the capacity of gigantic quantity of processing of data by merging the K-means and PSO ... See full document
8
Seeds Affinity Propagation Based on Text Clustering
... original Affinity Propagation algorithm, Jia et ...of Affinity Propagation is to reduce the number of message values that need to be ... See full document
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