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挖掘不确定和概率数据:问题、挑战、方法和应用

Mining Uncertain and Probabilistic Data: problems, Challenges, Methods, and Applications
课程网址: http://videolectures.net/kdd08_pei_mupd/  
主讲教师: Jian Pei, Ming Hua
开课单位: 西蒙弗雷泽大学
开课时间: 2008-09-26
课程语种: 英语
中文简介:
不确定的数据是一些重要应用所固有的,例如环境监测,市场分析和定量经济学研究。这些应用中的不确定数据通常是由数据随机性和不完整性,测量设备的限制,数据更新延迟等因素引起的。由于这些应用的重要性以及收集和积累的不确定数据的快速增加,分析和挖掘大不确定数据的集合已成为一项重要任务,并引起了数据挖掘界越来越多的关注。在本教程中,我们将对挖掘不确定性和概率数据的动机/应用,问题,挑战,基本原则和现有技术方法进行系统调查。我们将通过不确定数据分析的几个有趣的实际应用来激励调查。为了设定阶段,我们将简要讨论不确定和概率数据的两个主要模型。我们将介绍几个关于不确定数据的重要数据挖掘任务,包括聚类,分类,频繁模式挖掘和在线分析处理(OLAP)。对于每项任务,我们将分析不确定和概率数据以及最先进解决方案所带来的挑战。
课程简介: Uncertain data are inherent in some important applications, such as environmental surveillance, market analysis, and quantitative economics research. Uncertain data in those applications are generally caused by factors like data randomness and incompleteness, limitations of measuring equipment, delayed data updates, etc. Due to the importance of those applications and the rapidly increasing amount of uncertain data collected and accumulated, analyzing and mining large collections of uncertain data have become an important task and attracted more and more interest from the data mining community. In this tutorial, we will give a systematic survey on the motivations/applications, the problems, the challenges, the fundamental principles and the state-of-the-art methods of mining uncertain and probabilistic data. We will motivate the survey with several interesting practical applications of uncertain data analysis. To set the stage, we will discuss two major models for uncertain and probabilistic data briefly. We will cover several important data mining tasks on uncertain data, including clustering, classification, frequent pattern mining and online analytical processing (OLAP). For each task, we will analyze the challenges posed by uncertain and probabilistic data and the state-of-the-art solutions.
关 键 词: 不确定数据; 数据挖掘; 概率数据
课程来源: 视频讲座网
最后编审: 2019-05-09:lxf
阅读次数: 37