Shift Window FPTree - An Efficient Stream Mining Algorithm

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Deepak K Mishra 1,* Varsha Sharma 1

1. School of Information Technology, RGPV, Bhopal MP-462036, India

* Corresponding author.


Received: 12 May 2015 / Revised: 16 Jun. 2015 / Accepted: 3 Aug. 2015 / Published: 8 Sep. 2015

Index Terms

Data stream mining, flow of data, continues mining


Breathless flow in data collection and storage mechanism has enabled Firms to heap up a massive amount of data. In many cases, these huge volumes of data can be mined for fascinating and applicable information in a wide range of applications. When the arrival of data is fast as well in a large bunches in term of amount, this lead major problem to go through this data in both the circumstances in store it and in extracting the useful information from it. To taking under these issues continues mining or stream mining is a best way. Data steam mining allows to not storing the entire data for future prediction which lead to overcome the e-vestige and unnecessary storage overhead. But there is no such way in literature to mine continues data direct, so first one make it feasible accordingly and then mine it. Here in this paper we present an algorithm which handle stream data in very effective manner.

Cite This Paper

Deepak K Mishra, Varsha Sharma,"Shift Window FPTree - An Efficient Stream Mining Algorithm", IJEME, vol.5, no.4, pp.13-20, 2015. DOI: 10.5815/ijeme.2015.04.02


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