@inproceedings{ddd2be3888d54462b008c708cad0c706,
title = "Mining frequent pattern based on fading factor in data streams",
abstract = "In order to improve the mining efficiency of frequent patterns in data streams, we present an algorithm DS-FPM for mining frequent patterns in data streams. First, a data structure DSFP-tree is constructed and the data stream is divided into a set of segments, then potential frequent itemsets on each segment are obtained by IGFA algorithm, while the generated itemsets and the remaining itemsets of DSFP-tree generated by the earlier segment and sampled by fading factor are stored in new DSFP-tree, finally, the frequent patterns in the data stream can be rapidly found by a breadth-first search strategy. The experimental result shows that the execution efficiency of DS-FPM is better than that of FPIL-STREAM algorithm.",
keywords = "Data streams, Fading factor, Frequent pattern",
author = "Ren, \{Jia Dong\} and He, \{Hui Ling\} and Hu, \{Chang Zhen\} and Xu, \{Li Na\} and Wang, \{Li Bo\}",
year = "2009",
doi = "10.1109/ICMLC.2009.5212115",
language = "English",
isbn = "9781424437030",
series = "Proceedings of the 2009 International Conference on Machine Learning and Cybernetics",
pages = "2250--2254",
booktitle = "Proceedings of the 2009 International Conference on Machine Learning and Cybernetics",
note = "2009 International Conference on Machine Learning and Cybernetics ; Conference date: 12-07-2009 Through 15-07-2009",
}