AISB convention 2017

  In the run up to AISB2017 convention, I've asked Joanna Bryson, from the organising team, to answer few questions about the convention and what comes with it. Mohammad Majid al-Rifaie (https://twitter.com/mohmaj) Tu...


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Harold Cohen

Harold Cohen, tireless computer art pioneer dies at 87   Harold Cohen at the Tate (1983) Aaron image in background   Harold Cohen died at 87 in his studio on 27th April 2016 in Encintias California, USA.The first time I hear...


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Dancing with Pixies?...

At TEDx Tottenham, London Mark Bishop (the former chair of the Society) demonstrates that if the ongoing EU flagship science project - the 1.6 billion dollar "Human Brain Project” - ultimately succeeds in understanding all as...


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Computerised Minds. ...

A video sponsored by the society discusses Searle's Chinese Room Argument (CRA) and the heated debates surrounding it. In this video, which is accessible to the general public and those with interest in AI, Olly's Philosophy Tube ...


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Connection Science

All individual members of The Society for the Study of Artificial Intelligence and Simulation of Behaviour have a personal subscription to the Taylor Francis journal Connection Science as part of their membership. How to Acce...


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Notice

AISB opportunities Bulletin Item

PhD Studentship in Language Technology, Monash University, Australia


PhD Studentship in Language Technology, Monash University, Australia

The User Modeling and Natural Language (UMNL) Group at Monash University has been granted an ARC Linkage Grant for a project entitled "Sentiment detection from opinion surveys -- the quest for customer and employee satisfaction".  This project has a Melbourne-based industry partner, GAPbuster Worldwide, who is a leading provider of customer experience management solutions. The project will address current challenges in automatic sentiment detection, including determining whether discourse is subjective, and if so, its topic, polarity, intensity and usefulness. Sentiment detection is used for discriminating fact from opinion in information gathering applications, and extracting prevalent opinions about items. The aim of the project is to develop computational mechanisms that detect sentiment from texts, and summarize the sentiment expressed in multiple texts. The developed techniques will be applied to textual feedback provided by customers and employees about different aspects of service industries. The PhD student will focus on novel techniques for detecting polarity, intensity and usefulness, using Machine Learning techniques such as classification, bootstrapping and data compression.  This is an excellent opportunity to work on a project with strong practical as well as theoretical merits, while closely interacting with a commercial organization.

Successful candidates will have a 1st class honours degree in Computer Science, Statistics or equivalent, or a Masters degree with a major research component, an exceptional academic record, excellent programming skills, strong written and verbal communications skills, and an ability to work in a team environment.

The studentship is available for Australian citizens and permanent residents and New Zealand citizens, for a period of 3 years, earning ,627 per annum. The studentship must be taken up by March 31, 2009 at the latest. For further information and applications please contact Prof Ingrid Zukerman by email at Ingrid.Zukerman@infotech.monash.edu.au.

Deadline for application is October 31, 2008.