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Distributed frequent closed itemsets mining

  • Beihang University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

As many large organizations have multiple data sources and the scale of dataset becomes larger and larger, it is inevitable to carry out data mining in the distributed environment. In this paper, we address the problem of mining global frequent closed itemsets in distributed environment. A novel algorithm is proposed to obtain global frequent closed itemsets with exact frequency and it is shown that the algorithm can determine all the global frequent closed itemsets. A new data structure is developed to maintain the closed itemsets. Then an efficient implementation is provided based on the structure. Experimental results show that the proposed algorithm is effective.

Original languageEnglish
Title of host publicationProceedings - International Conference on Signal Image Technologies and Internet Based Systems, SITIS 2007
Pages43-50
Number of pages8
DOIs
StatePublished - 2007
Event3rd IEEE International Conference on Signal Image Technologies and Internet Based Systems, SITIS'07 - Jiangong Jinjiang, Shanghai, China
Duration: 16 Dec 200718 Dec 2007

Publication series

NameProceedings - International Conference on Signal Image Technologies and Internet Based Systems, SITIS 2007

Conference

Conference3rd IEEE International Conference on Signal Image Technologies and Internet Based Systems, SITIS'07
Country/TerritoryChina
CityJiangong Jinjiang, Shanghai
Period16/12/0718/12/07

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