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With the ever-increasing amount of data available on the internet, and so many people these days having an active online presence, social media and other websites are faced with the rapidly rising challenge of efficiently storing and potentially mining useful information from huge amounts of data. Dr Ying Zhou is researching how this can best be done, in an effort to facilitate better understanding of user behaviour patterns and thus improvement of the services provided to them.
"My research looks at how to store and obtain meaningful information from huge amounts of data. Examples of such bodies of data would be all the tweets sent by Twitter users, or all the photographs uploaded by Facebook users. The two major issues I'm trying to address are how to store this data durably and efficiently, and how to understand user behaviour patterns from the data.
"One of the aims of my research is to provide guidelines for the better management and use of the rich online data collected by large social networking websites. This data can reveal many interesting behavioural patterns, which in turn can help us to design better applications.
"I've also been working on improving the ranking of image query results using various contextual information. This will allow users to specify more subtle search or ranking criteria than are currently possible, such as the quality of the photographic images they are looking for.
"I'm passionate about this area of research, because it's practical and challenging and has a wide range of applications.
"I've been with the University of Sydney for nine years, and have been working in this field for around five years. As an academic staff member, I have access to the services of companies such as Amazon and IBM for my research. I also have the opportunity to work with bright students who have similar interests to mine."
With the ever-increasing amount of data available on the internet, and so many people these days having an active online presence, social media and other websites are faced with the rapidly rising challenge of efficiently storing and potentially mining useful information from huge amounts of data. Dr Ying Zhou is researching how this can best be done, in an effort to facilitate better understanding of user behaviour patterns and thus improvement of the services provided to them.
"My research looks at how to store and obtain meaningful information from huge amounts of data. Examples of such bodies of data would be all the tweets sent by Twitter users, or all the photographs uploaded by Facebook users. The two major issues I'm trying to address are how to store this data durably and efficiently, and how to understand user behaviour patterns from the data.
"One of the aims of my research is to provide guidelines for the better management and use of the rich online data collected by large social networking websites. This data can reveal many interesting behavioural patterns, which in turn can help us to design better applications.
"I've also been working on improving the ranking of image query results using various contextual information. This will allow users to specify more subtle search or ranking criteria than are currently possible, such as the quality of the photographic images they are looking for.
"I'm passionate about this area of research, because it's practical and challenging and has a wide range of applications.
"I've been with the University of Sydney for nine years, and have been working in this field for around five years. As an academic staff member, I have access to the services of companies such as Amazon and IBM for my research. I also have the opportunity to work with bright students who have similar interests to mine."
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BIGCOMP '16: Proceedings of the 2016 International Conference on Big Data and Smart Computing (BigComp)pp.61-68, (2016)
Services Computingpp.729-736, (2013)
Trust, Security and Privacy in Computing and Communicationspp.570-577, (2013)
Hao Zhong,Ying Zhou
ADC '12: Proceedings of the Twenty-Third Australasian Database Conference - Volume 124pp.109-116, (2012)
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Services Computingpp.298-305, (2012)
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