@inproceedings{9b545a3c6c99454aabefb606b14276ed,
title = "Multi-Hierarchies: Accurately computing realtime statistical measures on data streams",
abstract = "Computing statistical measures is a fundamental problem for mining data streams. Sometimes user wants to query the realtime correlation of data streams. In this paper, we introduce a system for computing realtime statistical measures of data streams. The system updates the realtime summaries which are used to compute affine relationships. We process every elements in every data stream only once, and get a similar accuracy rating compared with the static methods. To the best of our knowledge, we present a new method of computing affine relationship. Our system employs the multi-Hierarchies approach in the Sliding Window Model. First, we change AFCLST Clustering algorithm. Second, the Bottom-Up Updating algorithm updates the summaries which every hierarchy has stored after the Cumulative Calculation algorithms. Third, the Query Response algorithm uses summaries to compute the statistical measure. Finally, we establish the accuracy rating of our approach by performing several experiments on real datasets.",
author = "Penghe Qi and Shengfei Shi",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2014.; 9th International Conference on Wireless Algorithms, Systems and Applications, WASA 2014 ; Conference date: 23-06-2014 Through 25-06-2014",
year = "2014",
doi = "10.1007/978-3-319-07782-6\_65",
language = "英语",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "729--739",
editor = "Zhipeng Cai and Chaokun Wang and Siyao Cheng and Hongzhi Wang and Hong Gao",
booktitle = "Wireless Algorithms, Systems and Applications - 9th International Conference, WASA 2014, Proceedings",
address = "德国",
}