Frequent Items Mining in Data Streams

Abstract

The main goal of this research is to mine frequent items in data streams using ECLAT and Dynamic Itemset Mining algorithms and finding the performance and drawbacks of these two algorithms. Most commonly used traditional association rule mining algorithms are APRIORI algorithms, Partitioning algorithms, Pincer-Search algorithms, FPGrowth Algorithms and Dynamic Item Set Mining Algorithms, Eclat algorithms and so on. The performance factors used are number of frequent items generated using different thresholds and execution time. From the experimental results we come know that the performance of Éclat algorithm is better than the Dynamic Item Set Counting Algorithm.

Authors and Affiliations

Dr. S. Vijayarani, Ms. R. Prasannalakshmi

Keywords

Related Articles

Automated Medical Counter (AMC)

The need to go to the hospital, take all the necessary tests, consult a doctor and then buy their prescribed medicine takes more time. In the proposed system AMC (Automated Medical Counter) which works similarly to an A...

Key-Reinstatement Storms on Kids, A Keyed Incongruity Detection System

Most incongruity detection systems rely on machine learning algorithms to derive a model of normality that is later used to detect suspicious events. Various Learning schemes have been proposed to overcome this weakness...

Simulation of Distributed Power Flow Controller

The growing demand and the aging of networks make it desirable to control the power flow in power-transmission systems fast and reliably. The Load changes the voltage variation in transmission lines must be limited, oth...

A Novel Technique to Control Congestion in MANET using Knowledge Base Learning

MANET is mobile ad-hoc network in which mobile nodes can create the route from source to destination when they required. The path establishment from source to destination in mobile ad-hoc network is done on the basis of...

Low Power Design Techniques in CMOS Circuits : A Review

In the design of digital integrated circuits, power consumption is an important criterion. That indicates that low power circuits are now a days, emerging as an utmost priority in modern VLSI design. This is in contrast...

Download PDF file
  • EP ID EP20126
  • DOI -
  • Views 262
  • Downloads 4

How To Cite

Dr. S. Vijayarani, Ms. R. Prasannalakshmi (2015). Frequent Items Mining in Data Streams. International Journal for Research in Applied Science and Engineering Technology (IJRASET), 3(4), -. https://europub.co.uk./articles/-A-20126