Intelligent CRM through Conjoint Data Mining of Heterogeneous Sources. This project aims to investigate and develop techniques to improve customer relationship management (CRM) for public and private organisations. It aims to develop an intelligent framework to assist in adaptive marketing and management of customers. The framework is designed to manage multiple information resources for information sharing, and to synthesise knowledge through visualisation. Intended outcomes are standardised XM ....Intelligent CRM through Conjoint Data Mining of Heterogeneous Sources. This project aims to investigate and develop techniques to improve customer relationship management (CRM) for public and private organisations. It aims to develop an intelligent framework to assist in adaptive marketing and management of customers. The framework is designed to manage multiple information resources for information sharing, and to synthesise knowledge through visualisation. Intended outcomes are standardised XML profiles for the different data sets and business processes, novel techniques for conjoint mining of structured and semi-structured data, and adaptive business intelligence techniques. The results will be validated using large real-world data sets provided by the partner organisation.Read moreRead less
Harnessing Business Insights from Unstructured Customer Data. Resulting from customers’ widespread uptake of online channels to buy and communicate has been a surge in online reviews and social media posts. This textual information offers a viable alternative to surveys that Australian businesses currently conduct to obtain customer insights. However, these reviews are unstructured and require substantial pre-processing to extract underlying customer perceptions. Therefore, this project aims to ....Harnessing Business Insights from Unstructured Customer Data. Resulting from customers’ widespread uptake of online channels to buy and communicate has been a surge in online reviews and social media posts. This textual information offers a viable alternative to surveys that Australian businesses currently conduct to obtain customer insights. However, these reviews are unstructured and require substantial pre-processing to extract underlying customer perceptions. Therefore, this project aims to develop a novel machine learning approach to quantify the business-relevant information contained in textual information shared by customers online. This alternative approach will provide significant cost-saving benefits for a range of Australian companies, such as retailers, hotels, airlines and restaurants.Read moreRead less
Industrial Transformation Research Hubs - Grant ID: IH120100021
Funder
Australian Research Council
Funding Amount
$2,500,000.00
Summary
Pathways to market: transforming food industry futures through improved sensing, provenance and choice. Pathways to market: transforming food industry futures through improved sensing, provenance and choice. This Research Hub aims to transform the Australian food industry by demonstrating how new knowledge on food production and consumption generated through novel sensing technologies and advanced modelling techniques can be implemented in smart applications to power competitiveness, sustainabil ....Pathways to market: transforming food industry futures through improved sensing, provenance and choice. Pathways to market: transforming food industry futures through improved sensing, provenance and choice. This Research Hub aims to transform the Australian food industry by demonstrating how new knowledge on food production and consumption generated through novel sensing technologies and advanced modelling techniques can be implemented in smart applications to power competitiveness, sustainability and innovation in food value chains.Read moreRead less