Biography

1) Social media has become ubiquitous and vital for people networking and content sharing. Since social media can be construed as a form of collective wisdom, it is possible to exploit its power to predict real-world outcomes. Most social media analyses such as sentiment analysis for microblogs are often built as standalone, endpoint to endpoint applications. This makes the collaboration among distributed software and data service providers to create composite social analytic solutions difficult. This seminar first presents our system of systems service architecture for social media analytics that support and facilitate efficient collaboration, esp. analytics and data mining, among distributed service providers. Then we discuss a few data mining research projects that have been implemented on top of this architecture. For example, a recent study on collective attention in Twitter shows that an epidemic spreading of hashtags is predominantly driven by external factors. We extend a time-series form of susceptible-infectious-recovered (SIR) model to monitor microblog emerging outbreaks by considering both endogenous and exogenous drivers. In addition, we adopt partially labeled Dirichlet allocation (PLDA) model to generate both background latent topics and hashtag topics. It overcomes the problem of small available samples in hashtag analysis by including related but unlabeled tweets through inference. We standardize hashtag topic contagiousness measure as the estimated effective-reproduction-number (estimated R) derived from epidemiology. It is obtained by Bayesian parameter estimation. Guided by estimated R, one can profile and categorize emerging topics, and generate alerts on potential outbreaks. Experiment results confirm the effectiveness of this approach. Finally this seminar also demonstrates how the system of systems architecture facilitates effective mining on social, spatial and scientific data.

2) The recent boom in mobile device usage has provided more opportunities, competition and also increased complexities for content providers to monetize their information goods. Although mobile devices are becoming increasingly powerful, their hardware, software and connectivity are relatively more limited compared to desktop and enterprise systems. As a result, various content optimization services have emerged. This seminar focuses on content optimization services that modify and reorganize content to reduce the size of content and enhance the performance of processing on the content. For most content providers, this optimization process needs to be fast, scalable and yet aligned with their monetization strategies and cost requirements. Based on our experience on content optimization services, this seminar presents the basic theories, algorithms, implementations and economics related to these services. In particular, we present some practical considerations when these services are implemented on a cloud, which is typically perceived to be a cheaper and more scalable option compared to traditional dedicated servers.

Raymond Wong

Role
I am an Associate Professor at the School of Computer Science and Engineering, UNSW. During 2007-2010, I worked at NICTA . I am still collaborating with NICTA and involved in its spin-out company Cohesive Data Inc. I am also a regular Visiting Professor at Tsinghua University, Beijing.

Biography
I received my BSc from ANU, MPhil and PhD from HKUST. I held the Sir Edward Youde Graduate Fellowship. After my PhD, I was a postdoc at Stanford University and visiting scholar at UCLA. Before I joined UNSW, I worked at the computer science departments of the following universities: HKUST, Chinese University of Hong Kong, Macquarie University, and then University of Sydney.

Current Research
Areas of interest:
Mobile data management, mobile content optimization
Document processing, information retrieval
XML, data mining, graph

Teaching
At UNSW, I teach database courses: recently COMP9319 (Web Data Compression and Search) and COMP9311 (a postgraduate database course); previously COMP9314 (mainly XML Data Management); sometimes COMP9315 (i.e., Database System Implementation); and occasionally COMP3311 (an undergraduate database course).

Industry Consulting
Areas of expertise:
Mobile computing (e.g., mobile content adaptation, aggregation, management)
Database technologies (esp. advanced technologies such as XML databases,
middleware solutions etc.)
Document processing (e.g., storage, retrieval, search engines, versioning)

Graduated Research Students
Supervised honours theses: 50+
Dr. Raymond Wong http://www.cse.unsw.edu.au/~wong/
1 of 2 17/07/2014 12:16
6 of them obtained the University Medals
Graduated Research Masters student: 1
Graduated PhD students: 12

For Potential Research (Hons/PhD) Students
Please email me (wong at cse.unsw.edu.au).