Postgraduate Studentship
Reasoning with Uncertainty and Inconsistency in Structured Scientific Knowledge The Department of Electronics, Electrical Engineering and Computer Science A postgraduate studentship is available to work on an EPSRC-funded collaborative project entitled above (starting in January 2007) between (UCL) and (QUB). The award covers university fees for three years, plus an additional student stipend of £12,300.
Project Summary:
There is a huge and rapidly expanding amount of information available for scientists in various online resources. However, this wealth of information has created challenges for scientists who wish to locate and analyse knowledge from heterogeneous sources. Key problems that exist are that there is much uncertainty in individual sources of scientific knowledge, and many conflicts arising between different sources of scientific knowledge. Scientists therefore need tools that are tolerant of uncertainty and inconsistency in order to query and merge scientific knowledge.
This project aims to facilitate the analysis of scientific knowledge by the development of technology for structured scientific knowledge (SSK). SSK is represented by a set of SSK reports each of which is a structured report that describes one or more scientific datasources (such as one or more journal articles, empirical datasets, etc). The format is an XML document with textentries restricted to individual words, values or simple phrases in scientific terminology. SSK is
intended to help scientists understand the contents of a datasource. Each one contains summaritive information about the datasource (e.g. information from an abstract, summary of techniques used, etc) plus evaluative information about the datasource (eg. delineation of uncertainties and errors in the information source, qualifications of the key findings, etc). The summaritive information describes the
information provided by the authors of the datasource, and the evaluative information describes the information provided by the users or authors of the datasource. SSK can be constructed by hand, by information extraction technology, and as a result of analysing datasources.
In this project, we want to extend our existing work for merging and analysing heterogeneous structured information by harnessing formal theories for representing and reasoning with uncertain and inconsistent information. The result of the project will be a general theoretical framework for handling uncertainty and inconsistency in
SSK, and a demonstration of the framework in a prototype implementation for querying and merging potentially conflicting SSK from heterogeneous sources. More details of the project (including relevant research papers) can be found at
http://www.cs. ucl.ac.uk/ staff/a.hunter/ projects/ ssk/index. html
Applicants for the studentship should have a minimum of a 2:1 honours degree (or equivalent) in computer science, electronic engineering, or a related discipline with the appropriate experience and skills. An MPhil degree in Artificial Intelligence and research experience in Reasoning under Uncertainty are desirable.
To find out more, contact:
Dr Weiru Liu ( http://www.cs. qub.ac.uk/ ~W.Liu)
Computer Science
Queen's University Belfast
Tel: 02890 974896
Fax: 02890 975666
email: w.liu@qub.ac. uk
Application Forms can be downloaded at the following address
http://www.cs. qub.ac.uk/ ~W.Liu/QUBApplic ationForm. pdf
Guideline Notes can be found at http://www.qub. ac.uk/pao/ cast.htm
A completed Application Form and an up-to-date CV (including especially information that is not reflected on the Application Form) should be sent to: Ms Evelyn Milliken, The Postgraduate Officer, SARC Building, The Department of Electronics, Electrical Engineering and Computer Science Queen's University Belfast, Belfast, BT7 1NN, Northern Ireland, UK Tel: 028 9097 5464
Please indicate in the Financial Arrangement section on the Application Form that you are applying for the studentship to work on the above project.
The closing date for receipt of applications is Friday 10 November 2006
[sursa beasiswa]
