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Author:

Liu, Yunfeng (Liu, Yunfeng.) | Ke, Lin (Ke, Lin.) | Yuan, Yongke (Yuan, Yongke.)

Indexed by:

CPCI-S EI Scopus

Abstract:

The data pretreatment to reduce the redundancy of data and eliminate the data imprecise is the bottleneck in data mining. This article uses the superiority of the Rough Set model to eliminate the data imprecise, reduce the redundancy as far as possible in the data pretreatment and reduces the data capacity by the deduction of the attributes and deduction of values. It has also laid the foundation for the following data mining algorithm to reduce the time of process. By the example proof it is one better algorithm according to incomplete and redundancy data processing.

Keyword:

Attribute deduct Rough set Value deduct Pretreatment CRM Data mining

Author Community:

  • [ 1 ] [Liu, Yunfeng]Beijing Univ Technol, Coll Econ & Management, Beijing 100124, Peoples R China
  • [ 2 ] [Ke, Lin]Beijing Univ Technol, Coll Econ & Management, Beijing 100124, Peoples R China
  • [ 3 ] [Yuan, Yongke]Beijing Univ Technol, Coll Econ & Management, Beijing 100124, Peoples R China

Reprint Author's Address:

  • [Liu, Yunfeng]Beijing Univ Technol, Coll Econ & Management, Beijing 100124, Peoples R China

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Source :

INTERNATIONAL CONFERENCE ON ADVANCED COMPUTER CONTROL : ICACC 2009 - PROCEEDINGS

Year: 2009

Page: 92-97

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: 8

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