澳大利亚皇家墨尔本理工大学鲍芝峰博士报告

发布日期:2016-12-17 浏览次数: [字体: ]

报告题目:Exploring the Geospatial Data: When Visualization Meets Query Processing

报告人鲍芝峰博士

                澳大利亚皇家墨尔本理工大学计算机学院助理教授

报告时间:20161219日(周一)上午9:30

报告地点:明理楼402

报告人简介:

鲍芝峰博士现任澳大利亚皇家墨尔本理工大学计算机学院助理教授(永久教职)。于20062011取得新加坡国立大学计算机科学专业的荣誉学士和博士学位。目前研究兴趣:地理空间数据和轨迹数据上的数据管理和查询,流数据查询分析,互动可视化数据分析,以及数据整合和清洗。研究目的:提高数据的可用性。发表论文50余篇,其中20余篇CCF-A类论文,诸如数据库和信息检索顶级会议和期刊(SIGMOD, VLDB, ICDE, SIGIR, WWW, TKDE),20余篇CCF-B类论文。主要荣誉:2011年新加坡国立大学计算机学院最佳博士论文奖唯一获得者;新加坡信息发展局科技金牌;2015Google Faculty Research Award2篇最佳论文,4篇最佳论文提名。鲍博士的研究受到澳大利亚自然科学基金重点基金,Google Research Grant的资助,其中2016年获得200万科研经费的资助。社会兼职:近年来担任顶级会议的程序委员会委员,诸如VLDB,ICDE,SIGIR,IJCAI。任DASFAA 2017workshop track chairAPWEB 2016Demo Track ChairADMA 2016最佳论文评委会主席。个人主页:https://sites.google.com/site/baozhifengcs/; http://www.baozhifeng.net/

 

摘要:

In this talk, I will first introduce the most recent system we have built for an interactive and visualized exploration of the location-centered real estate data in Australia for the last ten years (http://115.146.89.158/). Then, I will adopt a top-down approach from real applications to fundamental research problems, to illustrate several research achievements on seamlessly combining data visualization and data management techniques to enhance the usability of geospatial data. In particular: (1) problem - how to continuously (7*24) monitor the trending areas and houses based on user’s spatial range and KNN queries in streaming fashion; significance - facilitate buyers to find a desired property and for sellers to find the best time to enter the market to sell the house. (2) Problem - How to achieve Efficient selection of Geospatial data on maps for Interactive Visualized Exploration; significance - to achieve the goal of representativeness, visibility, zoom consistency and movement consistency in one basket. (3) Problem – How different visualization designs help user find interesting patterns, help data cleaning, etc. Last, if time allows I will talk about our recent work on exploring the activity trajectory data for interactive trip planning.