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Author:

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

Indexed by:

CPCI-S

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.

Keyword:

frequent pattern mining data stream semi structured data

Author Community:

  • [ 1 ] [Tong, Ziqi]Beijing Univ Technol, Fac Informat Technol, Beijing, Peoples R China
  • [ 2 ] [Liao, Husheng]Beijing Univ Technol, Fac Informat Technol, Beijing, Peoples R China
  • [ 3 ] [Jin, Xueyun]Beijing Univ Technol, Fac Informat Technol, Beijing, Peoples R China

Reprint Author's Address:

  • [Tong, Ziqi]Beijing Univ Technol, Fac Informat Technol, Beijing, Peoples R China

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Source :

2017 IEEE 2ND INTERNATIONAL CONFERENCE ON BIG DATA ANALYSIS (ICBDA)

Year: 2017

Page: 274-280

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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