Behaviour modelling and social computing

 

Behaviour modelling and social computing are two fundamental research directions. Behaviour modelling is to derive user behavioural patterns, preferences, profiles from user behaviours and user generated textual data, while social computing is to analyse the social characteristics and trends demonstrated from intra-human or human-computer interactions.

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Visual Data Analytics

 

Visualization and visual analytics have been introduced both in academia and industry: 1) to provide a clear view of users diverse behavior, transactions monitoring, premium fluctuations, and in complex everyday decision-making, 2) to characterize data, user and task, and 3) discovering imbalances and monitoring risk. 

 

From our research group, we continuously publish research papers on these two topics and apply the developed techniques to help our industry partners with their business problems. Examples including anti-selection detection (Zurich One-Path), spam behaviour detection (Toutiao), and product/action recommendations (Yozo,https://www.yozo.com.au/). Specifically, our strengths include

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• Identifying misbehaviours or abnormal behaviours from a population

• Discovering the underlying behaviour patterns in a population

• Design a new visual analytics solutions (VAS)

• Recommending actions/items based on the underlying patterns

• Techniques: topic modelling, representation learning and embedding, rule mining, sequential pattern mining, anomaly detection, time series analysis.