Survey on Big Data as Frequent Itemset Mining Technique

Authors

  • Tamanna Jethava Department of Information & Technology Parul Institute of Engineering & Technology, Baroda, Gujarat, India
  • Rahul Joshi Department of Information & Technology Parul Institute of Engineering & Technology, Baroda, Gujarat, India

Keywords:

Mining of frequent itemset, Big Data, MapReduce, Hadoop platform, HDFS

Abstract

Frequent Item sets plays an essential role in many Data Mining tasks that try to find interesting
patterns from database. Typically it refers to a set of items that frequently appear together in transaction
dataset. There are several Mining algorithm are being used for frequent item set mining ,yet most do not
scale to the type of data we are presented with today, so called ―BIG DATA‖. Big Data is collection of large
data sets. Our approach is to work on frequent item set mining over the large dataset with scalable and
speedy way. Big Data basically work with Map Reduce along with HDFS is used to find out frequent item
sets from Big Data on large cluster. This paper focus on using pre-processing & mining algorithm as hybrid
approach for big data over Hadoop platform. Also survey on big data mining with New algorithm which
Provide scalability & effectiveness .Also increases it‘s time complexity with the help of parallel processing
over cluster on Hadoop.

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Published

2016-05-25

How to Cite

Tamanna Jethava, & Rahul Joshi. (2016). Survey on Big Data as Frequent Itemset Mining Technique. International Journal of Advance Research in Engineering, Science & Technology, 3(5), 705–709. Retrieved from https://ijarest.org/index.php/ijarest/article/view/691

Issue

Vol. 3 No. 5 (2016): Volume: 03, Issue: 05 - May, 2016.

Section

Articles