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Applications are invited for two fully funded, three year PhD studentships
in the School of Computing at the Dublin Institute of Technology.
The project is in the area of machine learning for text classification and
more specifically case base maintenance. Because case-based classification
techniques are local learners they are particularly susceptible to the
problem of noisy training data. Previous work by the project leader has
shown that in certain domains, particularly spam filtering, standard
case-base editing techniques are unsuitable. This project aims to
investigate why the newly developed blame-based noise reduction technique is
particularly successful in the spam domain and whether its success can be
transferred to the broader, but related, domains of text classification and
fraud detection. Furthermore, the project will investigate whether the
techniques of feature free learning and active learning can be applied to
the noise reduction problem.
Applicants for these studentships are expected to have a good honours degree
in computer science or a related discipline, excellent technical and
programming skills and strong written and spoken English. Previous
experience of artificial intelligence or machine learning is desirable but
not essential.
The grant covers a studentship of €16,000 per year plus all fees. For
further information on the project contact Dr Sarah Jane Delany (
www.comp.dit.ie/sjdelany/) or Dr Brian Mac Namee (www.comp.dit.ie/bmacnamee/).
Formal applications can be made through the Postgraduate Research Office in
Dublin Institute of Technology www.dit.ie/DIT/study/graduate/research/.
Applicants should complete the Funded Postgraduate Research Application
Form.
The closing date for applications is *15/6/2007* with the project proposed
to start on 1/9/2007.
in the School of Computing at the Dublin Institute of Technology.
The project is in the area of machine learning for text classification and
more specifically case base maintenance. Because case-based classification
techniques are local learners they are particularly susceptible to the
problem of noisy training data. Previous work by the project leader has
shown that in certain domains, particularly spam filtering, standard
case-base editing techniques are unsuitable. This project aims to
investigate why the newly developed blame-based noise reduction technique is
particularly successful in the spam domain and whether its success can be
transferred to the broader, but related, domains of text classification and
fraud detection. Furthermore, the project will investigate whether the
techniques of feature free learning and active learning can be applied to
the noise reduction problem.
Applicants for these studentships are expected to have a good honours degree
in computer science or a related discipline, excellent technical and
programming skills and strong written and spoken English. Previous
experience of artificial intelligence or machine learning is desirable but
not essential.
The grant covers a studentship of €16,000 per year plus all fees. For
further information on the project contact Dr Sarah Jane Delany (
www.comp.dit.ie/sjdelany/) or Dr Brian Mac Namee (www.comp.dit.ie/bmacnamee/).
Formal applications can be made through the Postgraduate Research Office in
Dublin Institute of Technology www.dit.ie/DIT/study/graduate/research/.
Applicants should complete the Funded Postgraduate Research Application
Form.
The closing date for applications is *15/6/2007* with the project proposed
to start on 1/9/2007.