DocumentCode :
3260477
Title :
Mining the Future: Predicting Itemsets´ Support of Association Rules Mining
Author :
Guirguis, Shenoda ; Ahmed, Khalil M. ; El Makky, Nagwa M. ; Hafez, Alaaeldin M.
Author_Institution :
Dept. of Comput. Sci., Pittsburgh Univ., PA
fYear :
2006
fDate :
18-22 Dec. 2006
Firstpage :
474
Lastpage :
478
Abstract :
This paper proposes a novel research dimension in the field of data mining, which is mining the future data before its arrival, or in other words: predicting association rules ahead before the arrival of the data. To achieve that, we need only predict the itemsets´ support, upon which association rules could be easily produced. A time series analysis approach (MFTP) is proposed to perform itemsets´ support prediction task. The proposed technique outperforms other prediction techniques for short history. The conducted performance study showed good prediction accuracy and response time. Thus, we provide a new tool to provide more information in the decision support field
Keywords :
data mining; time series; MFTP; data mining; itemsets; time series analysis approach; Association rules; Computer science; Data mining; Databases; Expert systems; History; Itemsets; Neural networks; Predictive models; Time series analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Data Mining Workshops, 2006. ICDM Workshops 2006. Sixth IEEE International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
0-7695-2702-7
Type :
conf
DOI :
10.1109/ICDMW.2006.116
Filename :
4063674
Link To Document :
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