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Author:

Zhao, Mingru (Zhao, Mingru.) | Sun, Yuan (Sun, Yuan.) | Guo, Jian (Guo, Jian.) | Dong, Pingping (Dong, Pingping.)

Indexed by:

CPCI-S EI Scopus

Abstract:

Frequent itemsets mining is an important data mining task and a focused theme in data mining research. Apriori algorithm is one of the most important algorithm of mining frequent itemsets. However, the Apriori algorithm scans the database too many times, so its efficiency is relatively low. The paper has therefore conducted a research on the mining frequent itemsets algorithm based on a across linker. Through comparing with the classical algorithm, the improved algorithm has obvious advantages.

Keyword:

association rules across linker Apriori algorithm frequent itemset

Author Community:

  • [ 1 ] [Zhao, Mingru]Beijing Univ Technol, Coll Comp Sci, Beijing, Peoples R China
  • [ 2 ] [Sun, Yuan]Sch Iformat Beijing Wuzi Univ, Beijing, Peoples R China
  • [ 3 ] [Guo, Jian]Sch Iformat Beijing Wuzi Univ, Beijing, Peoples R China
  • [ 4 ] [Dong, Pingping]Sch Iformat Beijing Wuzi Univ, Beijing, Peoples R China

Reprint Author's Address:

  • [Zhao, Mingru]Beijing Univ Technol, Coll Comp Sci, Beijing, Peoples R China

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Source :

MECHANICAL ENGINEERING AND INTELLIGENT SYSTEMS, PTS 1 AND 2

ISSN: 1660-9336

Year: 2012

Volume: 195-196

Page: 984-,

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: 6

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