Sentiment detection from opinion surveys -- the quest for customer and employee satisfaction. The research will yield improved international standing through scientific advances disseminated through high impact refereed publications and open source software. The advances made through the application of sophisticated probabilistic techniques to Language Technology problems will attract post-graduate students, and promote commercial interest. The demonstration prototype will provide proof of conce ....Sentiment detection from opinion surveys -- the quest for customer and employee satisfaction. The research will yield improved international standing through scientific advances disseminated through high impact refereed publications and open source software. The advances made through the application of sophisticated probabilistic techniques to Language Technology problems will attract post-graduate students, and promote commercial interest. The demonstration prototype will provide proof of concept of an application that enables business intelligence to automatically process free-form feedback from customers and employees, with resultant recommendations leading to increased customer and employee satisfaction. The applicability of the outcomes of this research to service industries will further improve Australia's service reputation.Read moreRead less
Deja-Vu -- A mechanism for constructing dialogue memory for resource-bounded agents. The ability to provide contextual information during interactions with computer systems has great potential to improve the overall experience for users. We propose to develop such an ability in the form of an automatically generated, continuously updated ``dialogue memory'', which may reside at server sites or in the PDAs of individual users. This memory will be generated by means of a novel approach which combi ....Deja-Vu -- A mechanism for constructing dialogue memory for resource-bounded agents. The ability to provide contextual information during interactions with computer systems has great potential to improve the overall experience for users. We propose to develop such an ability in the form of an automatically generated, continuously updated ``dialogue memory'', which may reside at server sites or in the PDAs of individual users. This memory will be generated by means of a novel approach which combines Natural Language techniques to extract dialogue features, model-selection techniques to cluster related dialogues, and cognitive modeling techniques to prune the resultant memories. The implemented computer system will be tested in the domain of trouble-shooting dialogues.Read moreRead less