Come and join our thriving community of research students in our new purpose-built research laboratory.
The aim of this research is to propose a solution to the problem of automated review classification and analysis for mobile apps. Reviews are written in unstructured natural language, which makes using existing Natural Language Processing tools difficult. Also the sets of reviews tend to be unbalanced (with many reviews for some apps, for example, but very few for others). This makes it difficult to apply many machine learning techniques.
The objectives of the PhD are to:
• design and implement tools and techniques that will automatically classify and analyse reviews • evaluate the effectiveness and efficiency of the new tools and techniques.
A systematic mapping study will be performed. This will be followed by software development and validation. The experimental work will be evaluated using appropriate metrics (such as Precision and Recall).
The Applied Software Engineering Research Group is part of the Department of Computing in the Faculty of Technology, Design and Environment. The Department provides undergraduate and postgraduate degrees in Computer Science and related disciplines. Details about the Department can be found at http://cct.brookes.ac.uk/
We are looking for enthusiastic candidates with:
• a solid background in Computer Science, shown by a good BSc: 2.1 or above and/or an MSc degree;
• a solid background in Mathematics; knowledge of software engineering methods;
• an appreciation of empirical techniques; • good communication and collaboration skills.
As research deliverables we expect publications, software, and a PhD thesis.
If you have any queries about this project, please contact: Rachel Harrison: [email protected]
There is more information about our research at http://cct.brookes.ac.uk/research/index.html
For details on how to apply and for details of the likely costs, please contact [email protected]
Claudia Iacob and Rachel Harrison, Retrieving and Analyzing Mobile Apps Feature Requests from Online Reviews, The 10th Working Conference on Mining Software Repositories (MSR 2013), May 18–19. San Francisco, California, USA Guzman, Emitza, and Wiem Maalej. "How do users like this feature? a fine grained sentiment analysis of app reviews." Requirements Engineering Conference (RE), 2014 IEEE 22nd International. IEEE, 2014.