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華南師范大學(xué)計(jì)算機(jī)學(xué)院學(xué)術(shù)報(bào)告通知
來(lái)源: 朱佳/
浙江師范大學(xué)
7352
15
0
2016-10-13

歡迎各位有興趣的朋友來(lái)聽(tīng):)


題目:Enhancing the Usability of Data

報(bào)告人:Zhifeng Bao(鮑芝峰博士)

              School of CSIT, RMIT University

              (澳大利亞墨爾本皇家理工大學(xué)計(jì)算機(jī)與信息技術(shù)學(xué)院)

地點(diǎn):學(xué)院101會(huì)議室

時(shí)間:20161017日下午2:30

學(xué)術(shù)報(bào)告簡(jiǎn)介Big data is now around every corner of our life - data is heterogeneous, of large volume and high rate of change. A very demanding task is how to make the data usable to data consumers. Data cannot make one's life better unless we provide her a way to find her expected 'needle' in such big data ocean. In this talk, I would like to give an overview of my works on improving the usability over heterogeneous data. In particular, we will talk about the usability and performance issues on structured data (mismatch problem), spatial-textual data (fuzzy type-ahead search problem), spatio-temporal data (activity trajectory search problem), and graph data (e.g. personalized realtime search over social media). Last I will introduce the system we are building for an interactive and visualized exploration of the location-centered real estate data in Australia for the last ten years.

報(bào)告人簡(jiǎn)介Zhifeng Bao is an assistant professor in School of Computer Science & IT, RMIT University, Australia. He received his PhD from the CS Dept at National University of Singapore in 2011. Zhifeng was the recipient of the Best PhD Thesis Award in School of Computing and was the winner of the Singapore IDA (Infocomm Development Authority) gold medal. His research was supported by various researching funding such as Google faculty research grant. He has been committing himself to the task of "how to make data usable", including structured data (e.g. relational data), semi-structured data (e.g. XML), unstructured data (e.g. text), spatial data and graph data (e.g. social network). He focused on building general yet efficient frameworks to support these usability modules, without breaking the traditional storage and indexing scheme for the underlying data. He has served the program committee of top conferences in Database and Information Retrieval such as VLDB, ICDE, SIGIR, as well as demo track chair of APWEB16 and workshop track chair of DASFAA17. He got Four Best Paper Award Nominations in ICDE 2009, DASFAA 2012, CIKM 2014, ER 2014, and most recently he was awarded the Best Student paper Award and the Best Demo Paper Award in ADC 2016.



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