Knowledge capturing and exploitation in social big data
The era of big data is creating a revolutionary opportunity for turning larger-sized datasets with high-velocity and diverse structures into real benefit across many domains, such as finance prediction, weather forecasting, disaster prevention, education and health care. Studies show that on average Web user spends two and a half hours daily on social media, and their activity reveals a great deal about what makes them tick. Social Networks become important sources of people “big data”, including demographic, location information, and data about people’s interests, tastes, and habits. One of the biggest challenges in exploiting social big data is how to capture knowledge from the massive amount of data where conventional data management methods would be incapable of handling, and exploit the inherent knowledge effectively to those who will benefit from it.
We will investigate how to:
Develop innovative ideas to generate insightful queries over social big data, so as to facilitate better visualisation and decision formulation and
How to develop inconsistency tolerant query answering approaches to social big data, where relevant knowledge, such as events and contexts, will be exploited to support customised applications of social big data.
The outcome of the project will be evaluated in terms of both performance and quality with comparisons to state-of-the-art systems.
The successful applicant should have, or expect to have, an Honours Degree at 2.1 or above (or equivalent) in Hold a first degree in Computer Science, Mathematics, Engineering, Data Science or related disciplines. It is essential for student to have solid knowledge about one of the following disciplines of modern computer science and artificial intelligence: discrete mathematics, knowledge-based systems, machine learning. It is important for student to have basic understanding of modern database systems and distributed systems. Student should have good programming skills.
There is no funding attached to this project, it is for self-funded students only.
SOCIAL BIG DATA: What We Look Like To Each Of The Social Networks And Their Advertisers
Formal applications can be completed online: http://www.abdn.ac.uk/postgraduate/apply. You should apply for PhD in Computing Science, to ensure that your application is passed to the correct College for processing. Please ensure that you quote the project title and supervisor on the application form.
Informal inquiries can be made to Dr J Pan (firstname.lastname@example.org) with a copy of your curriculum vitae and cover letter. All general enquiries should be directed to the Graduate School Admissions Unit (email@example.com).