Postgraduate Studentship

Reasoning with Uncertainty and Inconsistency in Structured Scientific KnowledgeThe Department of Electronics, Electrical Engineering and Computer ScienceA postgraduate studentship is available to work on an EPSRC-fundedcollaborative project entitled above (starting in January 2007)between (UCL) and (QUB). The award covers university fees for threeyears, plus an additional student stipend of £12,300.

Project Summary

There is a huge and rapidly expanding amount of information availablefor scientists in various online resources. However, this wealth ofinformation has created challenges for scientists who wish to locateand analyse knowledge from heterogeneous sources. Key problems thatexist are that there is much uncertainty in individual sources ofscientific knowledge, and many conflicts arising between differentsources of scientific knowledge. Scientists therefore need tools thatare tolerant of uncertainty and inconsistency in order to query andmerge scientific knowledge.

This project aims to facilitate the analysis of scientific knowledgeby the development of technology for structured scientific knowledge(SSK). SSK is represented by a set of SSK reports each of which is astructured report that describes one or more scientific datasources(such as one or more journal articles, empirical datasets, etc). Theformat is an XML document with textentries restricted to individualwords, values or simple phrases in scientific terminology. SSK isintended 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) plusevaluative information about the datasource (eg. delineation ofuncertainties and errors in the information source, qualifications ofthe key findings, etc). The summaritive information describes theinformation provided by the authors of the datasource, and theevaluative information describes the information provided by the usersor authors of the datasource. SSK can be constructed by hand, byinformation extraction technology, and as a result of analysingdatasources.

In this project, we want to extend our existing work for merging andanalysing heterogeneous structured information by harnessing formaltheories for representing and reasoning with uncertain andinconsistent information. The result of the project will be a generaltheoretical framework for handling uncertainty and inconsistency inSSK, and a demonstration of the framework in a prototypeimplementation for querying and merging potentially conflicting SSKfrom heterogeneous sources. More details of the project (includingrelevant research papers) can be found athttp://www.cs.ucl.ac.uk/staff/a.hunter/projects/ssk/index.html

Applicants for the studentship should have a minimum of a 2:1 honoursdegree (or equivalent) in computer science, electronic engineering, ora related discipline with the appropriate experience and skills. AnMPhil degree in Artificial Intelligence and research experience inReasoning 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/QUBApplicationForm.pdf

Guideline Notes can be found at http://www.qub.ac.uk/pao/cast.htmA completed Application Form and an up-to-date CV (includingespecially information that is not reflected on the Application Form)should be sent to:

Ms Evelyn Milliken, The Postgraduate Officer,
SARCBuilding, The Department of Electronics,
Electrical Engineering andComputer Science Queen`s University Belfast,
Belfast, BT7 1NN,
Northern Ireland, UK
Tel: 028 9097 5464

Please indicate in the Financial Arrangement section on theApplication Form that you are applying for the studentship to work onthe above project.

The closing date for receipt of applications is Friday 10 November 2006.