Mining Association Rules Algorithm and its Application Based on Key Transactions

Zi Xian Wang; Guo Fu  Ma; Sheng Li Ma; Shuang Yin Li; Yu Si Cheng

doi:10.4028/www.scientific.net/AMR.945-949.3387

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 945-949Mining Association Rules Algorithm and its...

Mining Association Rules Algorithm and its Application Based on Key Transactions

Abstract:

Some of the classic correlation algorithm (such as Apriori algorithm, fp-growth algorithm), and some other improved algorithms, mostly for the general case. In this paper, the prison system in the case, by the definition of key items, key issues, and give a targeted mining method. We get a lot of actual data in a prison in Hebei Province and analyze the date according our method, the results of the analysis applied to practical guidance. Experiments show that the model for predicting the efficiency of security incidents has reached more than 85% effective in reducing the occurrence of security incidents.

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Periodical:

Advanced Materials Research (Volumes 945-949)

Pages:

3387-3390

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.945-949.3387

Citation:

Cite this paper

Online since:

June 2014

Authors:

Zi Xian Wang*, Guo Fu Ma, Sheng Li Ma, Shuang Yin Li, Yu Si Cheng

Keywords:

Association Rule, Data Mining (DM), Key Transaction

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* - Corresponding Author

References

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