Finding tendencies in streaming data using Big Data frequent itemset mining-Reference-Cited by-同舟云学术

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Finding tendencies in streaming data using Big Data frequent itemset mining

Published:2019-01 Issue: Volume:163 Page:666-674
ISSN:0950-7051
Container-title:Knowledge-Based Systems
language:en
Short-container-title:Knowledge-Based Systems

Author:

Fernandez-Basso Carlos,Francisco-Agra Abel J.,Martin-Bautista Maria J.,Dolores Ruiz M.

Funder

Spanish Ministry for Economy and Competitiveness

Andalusian Government (Junta de Andalucía)

European Research Council (ERC)

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Management Information Systems,Software

Reference32 articles.

1. Efficient mining of frequent itemsets in social network data based on mapreduce framework;Farzanyar,2013

2. Survey on NoSQL database;Han,2011

3. D. Borthakur, HDFS architecture guide, HADOOP APACHE PROJECT http://hadoop.apache.org/common/docs/current/hdfsdesign.pdf, 2008.

4. MapReduce: simplified data processing on large clusters;Dean;Commun. ACM,2008

5. Hadoop: The Definitive Guide;White,2012

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