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关系数据的统计建模

Statistical Modeling of Relational Data
课程网址: http://videolectures.net/kdd07_domingos_smord/  
主讲教师: Pedro Domingos
开课单位: 华盛顿大学
开课时间: 2007-08-12
课程语种: 英语
中文简介:
传统上,kdd关注的是从单个关系中挖掘数据。然而,大多数应用程序都涉及多个交互关系,无论是显式(在关系数据库中)还是隐式(在半结构化和多模式数据中)。例如,链接分析、社交网络、生物信息学、信息提取、安全性、无处不在的计算等。近年来,挖掘此类数据已成为KDD界极感兴趣的话题。关键的困难在于关系域中的数据不再是I.I.D(独立且分布相同),这使得统计建模变得非常复杂。然而,研究现在已经发展到可以使用健壮、易于使用的通用技术和语言来挖掘非I.I.D.数据的程度。本教程的目标是将这些概念和技术的足够子集添加到研究人员和从业者的工具包中。
课程简介: KDD has traditionally been concerned with mining data from a single relation. However, most applications involve multiple interacting relations, either explicitly (in relational databases) or implicitly (in semi-structured and multimodal data). Examples include link analysis, social networks, bioinformatics, information extraction, security, ubiquitous computing, etc. Mining such data has become a topic of keen interest in the KDD community in recent years. The key difficulty is that data in relational domains is no longer i.i.d. (independent and identically distributed), greatly complicating statistical modeling. However, research has now advanced to the point where robust, easy-to-use, general-purpose techniques and languages for mining non-i.i.d. data are available. The goal of this tutorial is to add a sufficient subset of these concepts and techniques to the toolkits of both researchers and practitioners.
关 键 词: 应用程序; 统计建模; 链接分析; 社交网络; 生物信息学
课程来源: 视频讲座网
最后编审: 2019-12-20:lxf
阅读次数: 43