首页> 外文会议>Proceedings of the 2007 International Conference on Machine Learning and Cybernetics >A METHOD FOR CONTINUOUS QUERY OVER DATA STREAM USING WAVELET SYNOPSIS
【24h】

A METHOD FOR CONTINUOUS QUERY OVER DATA STREAM USING WAVELET SYNOPSIS

机译:小波提要的数据流连续查询方法

获取原文

摘要

Continuous query is an important aspect for data stream management techniques.The focus is to design one-pass scan algorithm over dataset, maintain an effective synopsis data structures in memory which is far smaller than size of the whole dataset.With this data structure, approximate query result can be finished rapidly.A novel method for continuous query is presented in this paper, which is based on wavelet error tree synopsis.In this method, sliding window model is used, adaptive threshold is selected, and the wavelet coefficients in the sliding window can be incrementally updated.These make the method more efficient in memory and response time.It is suitable for not only streaming data but also large amount of historical data.An experiment using real power load dataset proves effectiveness of this method.
机译:连续查询是数据流管理技术的一个重要方面,重点是对数据集设计一次扫描算法,在内存中保持有效的概要数据结构,该数据结构远小于整个数据集的大小。查询结果可以快速完成。本文提出了一种基于小波误差树提要的连续查询新方法。该方法采用滑动窗口模型,选择自适应阈值,并在滑动中采用小波系数。窗口可以进行增量更新,这使该方法在内存和响应时间上更有效,不仅适用于流数据而且还适用于大量历史数据,使用实际功率负荷数据集进行的实验证明了该方法的有效性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号