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A Textual Entailment Approach for Sentiment Mining in Cyber-Security

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  • Full or part time
    Prof Mulvenna
    Dr Bi
  • Application Deadline
    No more applications being accepted
  • Funded PhD Project (European/UK Students Only)
    Funded PhD Project (European/UK Students Only)

About This PhD Project

Project Description

This is a Department for Employment and Learning (DEL) funded PhD Studentship in collaboration with Repknight Ltd (Weavers Court, Belfast, Northern Ireland).

Applications are invited for the following DEL-CAST studentship (Co-operative Awards in Science and Technology). The project available is in the Computer Science Research Institute in collaboration with Repknight Ltd and is tenable in the School of Computing and Mathematics, Faculty of Computing and Engineering at the Jordanstown Campus, Ulster University.

Background -

RepKnight provides a platform to detect and understand what is being said on the web through social media in real-time. The platform enables real-time analysis of social media data, to monitor tension and to identify threats, emerging events, providing users with an alert or an immediate world-view or hyper-local view of public opinion on key issues. Since establishment, the Company has secured and delivered contracts beyond what could have been expected of a young, small team, including contracts with the Home Office, Scottish Government, and Middle East countries. RepKnight was officially recognised as the most innovative security company in the UK in 2014, having been awarded the ADS Security Innovation Award at the Home Office.

The work required for the student by the company is to undertake research under the academic supervisors, reviewing the state of the arts of technologies and existing products as well as fundamental issues to the success of the product, and improve the company’s current sentiment analysis algorithms by incorporating advanced artificial intelligence technologies, including text entailment, natural language processing and advanced data analytics techniques.

Application -

Applicants should hold ordinary UK residence to be eligible for both fees and maintenance. Non UK residents who hold ordinary EU residence may also apply but if successful will receive fees only. All applicants should hold a first or upper second class honours degree in Computer Science or a related discipline. Successful candidates will enrol as of 1 March 2016 on a full-time research programme, of up to three years subject to satisfactory progress, leading to the award of the degree of Doctor of Philosophy.

The studentship will comprise tuition fees and a maintenance award (subject to UK residence status) 
of not less than £15,000 per annum, funded by DEL (the Department for Employment & Learning in NI) and Repknight Ltd.

The closing date for receipt of completed applications is 29 January 2016

Interviews will be held at the beginning of February 2016 (to be confirmed)

If you wish to discuss your proposal or receive advice on the research project please contact: 
Professor Maurice Mulvenna tel: 02890368602, email: [email protected], Dr Yaxin Bi, tel: 02890366582, email: [email protected]; Professor Hui Wang, tel: 02890368981, email: [email protected]

For further information on the application process please visit our website: 
http://study.ulster.ac.uk/postgraduate/applying.php
Apply online www.ulster.ac.uk/applyonline

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