An Improved Incremental Queue Association Rules for Mining Mass Text

Wen Chuan Yang; Qing Yi Qu; Peng Fei Ma

doi:10.4028/www.scientific.net/AMR.962-965.2687

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 962-965An Improved Incremental Queue Association Rules...

An Improved Incremental Queue Association Rules for Mining Mass Text

Abstract:

Association rules is an important data analysis and mining method, and the FP-Growth and the traditional FP-Tree algorithm is used in the full confidence of rules. This paper proposes a incremental queue algorithm models based on association rules, which is the improved FP4W-Growth algorithm. It is proposed and applied to the calculation the association text by the correlation of incremental queue. Its feasibility is validated by experiment. After optimization of the algorithm and model, it can find hidden and useful new information and new pattern. And those rules found in text can be potentially used as the scientific decision-making methods.

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Periodical:

Advanced Materials Research (Volumes 962-965)

Pages:

2687-2690

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.962-965.2687

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Online since:

June 2014

Authors:

Wen Chuan Yang, Qing Yi Qu, Peng Fei Ma

Keywords:

Association Mining, Full Confidence, Incremental Queue, Scientific Text

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