Dialogue-to-Action:Towards A Self-Evolving Enterprise Intelligent Assistant. The project aims to develop a novel Self-Evolving Enterprise Intelligent Assistant (EIA) by leveraging the Chatbot-based dialogue technique to acquire information, infer user intentions, understand languages, and determine subsequent actions to take through Dialogue-to-Action modelling. This new generation EIA is equipped with Artificial Generalised Intelligence, with a broad skill set able to tackle multiple business t ....Dialogue-to-Action:Towards A Self-Evolving Enterprise Intelligent Assistant. The project aims to develop a novel Self-Evolving Enterprise Intelligent Assistant (EIA) by leveraging the Chatbot-based dialogue technique to acquire information, infer user intentions, understand languages, and determine subsequent actions to take through Dialogue-to-Action modelling. This new generation EIA is equipped with Artificial Generalised Intelligence, with a broad skill set able to tackle multiple business tasks and handle fast-changing scenarios in business. The Self-Evolving EIA is a critical step on the path towards the future generation of EIA. Expected outcomes of this project are to develop adaptive EIA for Small and Medium Enterprise to improve their customer service quality.Read moreRead less
Deep Pattern Mining for Dynamic Real-time Enterprise Scale Pricing. This project aims to build a pricing framework, based on deep pattern mining, to enable dynamic real-time pricing for large enterprises. It aims to advance existing business intelligence pricing models from policy driven to achieve deep pattern driven real-time pricing. The deep pattern mining addresses critical and under-developed knowledge discovery and data mining issues. Detailed research topics include a probabilistic data ....Deep Pattern Mining for Dynamic Real-time Enterprise Scale Pricing. This project aims to build a pricing framework, based on deep pattern mining, to enable dynamic real-time pricing for large enterprises. It aims to advance existing business intelligence pricing models from policy driven to achieve deep pattern driven real-time pricing. The deep pattern mining addresses critical and under-developed knowledge discovery and data mining issues. Detailed research topics include a probabilistic data model, an extracted deep feature representation, a deep pattern mining algorithm, and a prototype system for pricing determination. The project outcomes aim to empower enterprises with real-time dynamic pricing capability, as well as building theoretical foundations to strengthen world leadership by Australian businesses.Read moreRead less
Mining complex concurrency relationship patterns for dynamic customer/asset interaction modelling through novel industrial behaviour networks . This project will develop novel data mining algorithms to model the evolution of concurrency relationships between customers and assets. It will take into account multiple aspect factors for a business such as seasonality, government policy, and other external events, for making fast, accurate, and efficient business decisions.