Advancing the state of the art in Argument Mining

Argument mining is the automatic identification and extraction of argumentative structure from within real world textual resources such as Web pages, Internet discourse, legal documents, or newspaper articles.

One of the challenges of argument mining is to construct a plausible model of argument structure that accurately reflects the argument made by the original author as there can be multiple different interpretations. Similarly, there are many techniques that individually identify different aspects of arguments but no single technique that can successfully and reliably mine arguments from arbitrary natural language resources. Furthermore, existing approaches do not explicitly take account of the defeasible nature of argument interpretation, that each technique might provide evidence to support or reject a specific argumentative interpretation of the source text.

This project will involve a detailed study of the structure of natural language arguments and evaluation of existing natural language understanding and machine learning techniques applied to argument mining in order to build a state of the art theoretical and applied model of Argument Mining. The novel contribution will be the construction of an evidence based, defeasible model of mined argument in which the evidence supporting each interpretation comes from the output of a suitable ensemble of argument mining techniques.

Academic qualifications

A second class honour degree or equivalent qualification in Software Engineering, Computer Science, Machine Learning, Artificial Intelligence.

English language requirement

IELTS score must be at least 6.5 (with not less than 6.0 in each of the four components). Other, equivalent qualifications will be accepted. Full details of the University's policy are available online.

Essential attributes

• Knowledge of Artificial Intelligence
• Good written and oral communication skills 
• Strong motivation, with evidence of independent research skills relevant to the project
• Good time management

Application process

Prospective applicants are encouraged to contact the supervisor, Dr Simon Wells ([Email Address Removed]) to discuss the content of the project and the fit with their qualifications and skills before preparing an application. 

The application must include: 

Research project outline of 2 pages (list of references excluded). The outline may provide details about

• Background and motivation, explaining the importance of the project, should be supported also by relevant literature. You can also discuss the applications you expect for the project results.
• Research questions or
• Methodology: types of data to be used, approach to data collection, and data analysis methods.
• List of references

The outline must be created solely by the applicant. Supervisors can only offer general discussions about the project idea without providing any additional support.

• Statement no longer than 1 page describing your motivations and fit with the project.
• Recent and complete curriculum vitae. The curriculum must include a declaration regarding the English language qualifications of the candidate.
• Supporting documents will have to be submitted by successful candidates.
• Two academic references (but if you have been out of education for more than three years, you may submit one academic and one professional reference), on the form can be downloaded here.

Applications can be submitted here.

Download a copy of the project details here.