Continuous intent tracking for virtual assistance using big contextual data. Recently launched Virtual Assistant products such as Amazon Echo and Google Home are commanded by voice and can call apps to do simple tasks like setting timers and playing music. The next-generation virtual assistants will recommend things to be done proactively rather than waiting for commands passively. This project aims to develop algorithms that can predict what a user intends to do and therefore help virtual assis ....Continuous intent tracking for virtual assistance using big contextual data. Recently launched Virtual Assistant products such as Amazon Echo and Google Home are commanded by voice and can call apps to do simple tasks like setting timers and playing music. The next-generation virtual assistants will recommend things to be done proactively rather than waiting for commands passively. This project aims to develop algorithms that can predict what a user intends to do and therefore help virtual assistants make recommendations that suit users’ needs accurately. It will benefit many service industry sectors of Australia by enabling virtual assistants to provide services proactively.Read moreRead less
On Effectively Answering Why and Why-not Questions in Databases. While the performance and functionality of database systems have gained dramatic improvement, research on improving usability still remains far behind, which results in huge cost of technical support to organisations. This project aims to improve the usability of database systems by effectively answering users' why and why-not questions on query results. This project will invent a novel and generalised model for expressing both the ....On Effectively Answering Why and Why-not Questions in Databases. While the performance and functionality of database systems have gained dramatic improvement, research on improving usability still remains far behind, which results in huge cost of technical support to organisations. This project aims to improve the usability of database systems by effectively answering users' why and why-not questions on query results. This project will invent a novel and generalised model for expressing both the why and why-not questions, efficient strategies for answering questions for complex queries and databases, and novel solutions to scenarios that involve multiple queries. The project will contribute greatly to the fundamental research in query refinement and deliver significant impact on related technology development. Read moreRead less