0


质量保证资源感知流挖掘模型

A Model for Quality Guaranteed Resource-Aware Stream Mining
课程网址: http://videolectures.net/ecml07_mohamed_mqgr/  
主讲教师: Mohamed Medhat Gaber
开课单位: 莫纳什大学
开课时间: 2008-01-29
课程语种: 英语
中文简介:
数据流以高速连续生成。大多数数据流挖掘技术通过使用适应和近似技术来解决这一挑战。适应现有资源是最近解决的问题。尽管这些技术保证了数据挖掘过程在资源限制下的连续性,但输出质量仍然是一个悬而未决的问题。本文提出了一种在保持资源有效消耗的同时保证产出质量的通用模型。该模型在给定可用资源的情况下,对输出质量进行估计。仅使用这些资源的一个子集,以确保最低的质量损失。该模型适用于任何数据流挖掘技术。
课程简介: Data streams are produced continuously at a high speed. Most data stream mining techniques address this challenge by using adaptation and approximation techniques. Adapting to available resources has been addressed recently. Although these techniques ensure the continuity of the data mining process under resource limitation, the quality of the output is still an open issue. In this paper, we propose a generic model that guarantees the quality of the output while maintaining efficient resource consumption. The model works on estimating the quality of the output given the available resources. Only a subset of these resources will be used that guarantees the minimum quality loss. The model is generalized for any data stream mining technique.
关 键 词: 计算机科学; 数据挖掘; 数据流
课程来源: 视频讲座网
最后编审: 2019-12-06:lxf
阅读次数: 27