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ISSN: 2395-1052 • IF: 7.883
ISSN: 2395-1052 | Impact Factor:IF: 7.883 | International Peer-Reviewed Open Access Journal
Research Topic

Mapr

20 Publications Matching this Keyword

Impact Factor
7.883
Mapr

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Papers tagged with "Mapr"

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Vol 2, Issue 6 (June 2016) Big Data

SIMPLIFIED PARALLEL DATA PROCESSING ON LARGE WEIGHTED ITEMSET USING MAPREDUCE

The Collections Of Data Are Often Wont To Growth And Accessibility Of The Information. Its Necessary To Have Been With Business And For The Society. Frequent Item Set Mining Is Associate With The Data Processing Techniques. That Has Been...

Sunitha S, Sahana Devi K J
Vol 2, Issue 6 (June 2016) Big Data Analytics

Improving performance of hadoop in handling small files

Hadoop Is An Open Source Software Stack For Processing Unstructured And Semi-structured Data Over The Cluster Of Commodity Hardware. It Is A Reliable, Scalable And Low Cost Solution For Storing And Processing Huge Amounts Of Data In A D...

Arshid Ahmed shah, Mangala C N
Vol 2, Issue 5 (May 2016) Data Mining, Hadoop

PARALLEL FIM USING HADOOP

Frequent Itemsets Mining (FIM)is The Initial Step For Deriving Association Rules. The Problem Related To FIM Is Its Significant Amount Of Time Consumption. When Datasets Become Excessively Large, Single Machine Algorithms Do Not Perform...

Suraj Ghadge, Pravin Durge, Vishal Bhosale, Sumit Mishra
Vol 2, Issue 5 (May 2016) Data Mining

MAP REDUCE RECOMMENDATION SYSTEM FOR WEB LOG ANALYTICS

Recommendation Systems Are Found In Many Applications And These Systems Usually Provide The User With A List Of Map Reduce Based On Preference And Prediction. By Combining Existing Datasets, Hybrid Recommendation Systems Can Be Develope...

R. Boomathi, S. Gowthami, A. Kanimozhi
Vol 2, Issue 4 (April 2016) Data Mining

A SURVEY ON DATA MINING AND ANALYSIS IN HADOOP AND HBASE

Data Mining Is A Process To Generate Pattern And Rules From Various Types Of Data Marts And Data Warehouses, In This Process There Are Several Steps Which Contains Data Cleaning Data Anomaly Detection Then Clean Data Is Mined With Vario...

Mrs. Amita V. Shah, Mr. Krunal Panchal

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