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Author:

Tong, Ziqi (Tong, Ziqi.) | Liao, Husheng (Liao, Husheng.) (Scholars:廖湖声) | Jin, Xueyun (Jin, Xueyun.)

Indexed by:

EI Scopus

Abstract:

This paper presented a frequent pattern mining algorithm SSDTreeMiner used in semi structured data streams. The algorithm gets the frequent pattern in the target time by using the adding and deleting principle and maintaining the sliding windows, at the same time, uses the time attenuation model to eliminate the influence of historical data in the mining process, compared with the traditional algorithms, the SSDTreeMiner algorithm can deal with high speed and complex data streams and complete mining tasks real-timely and efficiently. © 2017 IEEE.

Keyword:

Data streams Data mining Big data

Author Community:

  • [ 1 ] [Tong, Ziqi]Faculty of Information Technology, Beijing University of Technology, Beijing, China
  • [ 2 ] [Liao, Husheng]Faculty of Information Technology, Beijing University of Technology, Beijing, China
  • [ 3 ] [Jin, Xueyun]Faculty of Information Technology, Beijing University of Technology, Beijing, China

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Source :

Year: 2017

Page: 269-275

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 1

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 5

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