主講人簡介🕗：
支誌雄，現任澳大利亞聯邦科學與工業組織（CSIRO）Data61研究所，雲計算和傳感數據安全組的科研組長🕵🏼♂️。在加入CSIRO之前👈🏼👋🏻，他從普渡大學獲得博士學位，先後在Philips Research☺️、IBM Poughkeepsie、中國香港大學、新加坡國立大學👈、清華大學任職👮🏿，並擔任WCW 2004, AWCC 2004, IEEE SOSE 2006, ICSOC 2009, SCC 2009, SIE 2010, EDOC 2011, EDOC 2012, CWI 2012, SCC 2014, ICICS2016, and ICBE 2016等會議主席，已在國際知名會議和期刊上發表論文超過250篇，擁有6項已經產業化的美國專利。他目前的研究領域包括行為信息學和分析學，網絡安全，物聯網，雲計算、服務計算和社交網絡。
報告摘要：
Abstract: Under the era of Big Data, people have been exploring ways of realizing value from data at their fingertips. However, it is found that while collecting data is not difficult, value creation is often a big challenge. First, sensors and sensing techniques have been advancing rapidly for real time data collection with good enough accuracy. However, without efficient and effective ways to select, co-relate, integrate and transform multiple streaming data and their context information into manageable knowledge, these data are actually burdens instead of potentials to their owners. Second, despite numerous successful research efforts in data mining and machine learning, it is found that much less emphasis is put in the incorporation of domain knowledge into the data mining and pattern discovery processes, and in the use of behaviour genotypes such as loyalty and purchase power of customers to support final decision making. Third, related to the analytics platform, internet-of-things, service and cloud computing techniques are quite mature, and lots of machine learning algorithms are also widely available in both commercial and open source packages. However, how to use them for vertical service composition to provide “intelligence-as-a-service” for a given domain is still open for exploration. In this presentation, we will go into details of the current challenges of big data analytics and describe how behaviour analytics on trajectory data can help realize the value creation process from Big Data. In the discussion, both the science questions behind and the potential applications will be emphasized.
