First IEEE International Conference on Data Mining (ICDM'01) San Jose, California November 29-December 02 ISBN: 0-7695-1119-8
The choices for mining of decentralized data are numerous, and we have developed techniques to enumerate and optimize decentralized frequent itemset counting. In this paper, 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.
Citation:
Viviane Crestana Jensen, Nandit Soparkar, "Heuristic Optimization for Decentralized Frequent Itemset Counting," icdm, pp.613, First IEEE International Conference on Data Mining (ICDM'01), 2001 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||