Frequent Itemset Mining for Big Data in social media using ClustBigFIM algorithm

Frequent Itemset Mining for Big Data in social media using ClustBigFIM algorithm Abstract – Tremendous amount of data is getting explored through IOT (Internet of Things) from variety of sources such as sensor network, social media feed, internet applications, called as Big Data. Big Data cannot be handled by conventional tools and techniques. Social networks are becoming dominant in communications over internet. The Big Data mining is essential in order to extract value from massive amount of data which could give better insights using efficient techniques. Association Rule mining and…

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FastRAQ: A Fast Approach to Range-Aggregate Queries in Big Data Environments

FastRAQ: A Fast Approach to Range-Aggregate Queries in Big Data Environments Range-aggregate queries are to apply a certain aggregate function on all tuples within given query ranges. Existing approaches to range-aggregate queries are insufficient to quickly provide accurate results in big data environments. FastRAQ—a fast approach to range-aggregate queries is proposed in big data environments. FastRAQ first divides big data into independent partitions with a balanced partitioning algorithm, and then generates a local estimation sketch for each partition. When a range-aggregate query request arrives, FastRAQ obtains the result directly by…

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