Histograms and Wavelets for Fast Approximate Query Answering

Histograms and Wavelets for Fast Approximate Query Answering

时间：2011年11月25日 地点：九龙湖校区计算机楼313室

报告简介：

Methods for fast approximate query answering are an essential component of modern database management systems. All commercial database management systems have query optimizers that maintain statistical summaries of the data to quickly estimate the sizes of intermediate results and the costs of different query execution plans. In many online analytical processing (OLAP), data mining and data visualization applications, it is desirable to provide quick approximate answers to queries based on summarized information of the data. Histograms and wavelets are popular techniques that have been extensively studied for fast approximate query answering. In this talk, we will present two histogram techniques and one wavelet technique that outperform previous methods.

报告人简介：

分别于1994年、1997年和2004年获加拿大新不伦瑞克大学计算机学士、加拿大多伦多大学计算机硕士和博士学位，现为加拿大圣玛丽大学金融信息系统管理科学系副教授（终身教授）。主要从事数据挖掘、查询处理等方面研究。近五年内他在VLDB，Journal of Database Management，Knowledge and Information Systems等一流的期刊和会议上发表了60多篇学术论文，5篇学术专著章节，还是《Computers and Mathematics with Applications》、《Electronic Commerce Research Journal》、《IEEE Transactions on Computers》、《International Journal of Business Intelligence and Data Mining》等10个学术期刊和18个国际学术会议的审稿人，担任了《The 2010 International Conference on Data and Knowledge Engineering》、《The 13th International Business Information Management Association Conference on Knowledge Management and Innovation in Advancing Economies (2009)》等9个国际会议的程序委员会委员，并承担学术专著Encyclopedia of Data Warehousing and Mining的审稿人。

计算机网络和信息集成教育部重点实验室（东南大学）