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Visual > Text
时间:2019-09-27 15:48    点击:   所属单位:网络与信息安全学院
讲座名称 Visual > Text
讲座时间 2019-09-30 14:30:00
讲座地点 西安电子科技大学南校区行政辅楼一楼会议室
讲座人 Sourav S Bhowmick
讲座人介绍
Sourav S Bhowmick is an Associate Professor in the School of Computer Science and Engineering (SCSE), Nanyang Technological University. He leads the data management research group (DANTe) in SCSE. He was a Visiting Associate Professor at the Biological Engineering Division, Massachusetts Institute of Technology during 2007-2013. His research areas include data management, human-data interaction, data analytics, computational social science and network biology. He has published more than 90 papers in top-tier venues such as VLDB, SIGMOD, WWW, SIGIR, ACM MM, Bioinformatics, Biophysical Journal, and VLDB Journal. He has received Best Paper Awards at ACM CIKM 2004 and ACM BCB 2011 for papers related to evolution mining and biological network summarization, respectively. His work on in uence maximization was nominated for the best paper award in ACM SIGMOD 2015. His XML data management framework for biological data was adopted by a local startup HeliXense Pte Ltd in 2002. Sourav regularly serves as a reviewer for data management, data mining, and bioinformatics conferences (e.g., SIGMOD, VLDB) and journals (e.g., VLDB Journal, Bioinformatics). He has served as a program chair/co-chair of several international conferences including IEEE BigComp 2018, DASFAA 2014, DEXA 2009, and DEXA 2008. He has been keynote and tutorial speaker for several international conferences (including SIGMOD, VLDB, ER). Sourav is a co-recipient of the VLDB Service Award in 2018 from the VLDB Endowment for his contribution in designing an ecient PVLDB proceedings management framework. Recently, he has co-authored books on \Summarizing Biological Networks" and \Human Interaction with Graphs", which are published by Springer-Verlag (May 2017) and Morgan & Claypool (Aug 2018) publishers, respectively.
讲座内容
Since the inception of data management research in the 70s, both academic and commercial e orts have been heavily skewed towards query paradigm that is based on text. The underlying implicit (and sometimes explicit) assumption in this paradigm is that consumers of data management services are comfortable and skillful in formulating queries using textual languages. In this talk, we challenge this assumption and emphasis that humans are visual creatures since prehistoric times! We advocate that our querying services need to be \visually-aligned" and empower humans in wider communities with visual tools. As a byproduct of this paradigm, we highlight several novel functionalities and features a visual querying framework may potentially provide to consumers that are hard to realize in a classical text-based paradigm. Although we primarily focus on graph-structured data, the ideas are broadly applicable to other types of data.
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