DocumentCode
2335727
Title
Heuristic optimization for decentralized frequent itemset counting
Author
Jensen, Viviane Crestana ; Soparkar, Nandit
Author_Institution
Dept. of Electr. Eng. & Comput. Sci., Michigan Univ., Ann Arbor, MI, USA
fYear
2001
fDate
2001
Firstpage
613
Lastpage
614
Abstract
The choices for mining of decentralized data are numerous, and we have developed techniques to enumerate and optimize decentralized frequent itemset counting. We introduce our heuristic approach to improve the performance of such techniques developed in ways similar to query processing in database systems. We also describe empirical results that validate our heuristic techniques
Keywords
data mining; distributed algorithms; heuristic programming; optimisation; query processing; very large databases; database systems; decentralized data mining; decentralized frequent itemset counting; heuristic approach; heuristic optimization; heuristic techniques; query processing; Algebra; Computer science; Cost function; Data mining; Database systems; Demography; Itemsets; Merging; Partitioning algorithms; Query processing;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Mining, 2001. ICDM 2001, Proceedings IEEE International Conference on
Conference_Location
San Jose, CA
Print_ISBN
0-7695-1119-8
Type
conf
DOI
10.1109/ICDM.2001.989579
Filename
989579
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