Knowledge capturing and visualization from 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 present the inherent knowledge effectively to those who will benefit from it.
We envisage two tasks in this PhD project:
(1) To develop innovative techniques and data-intensive analysis solutions for discovering knowledge and information from social big data (mainly textual and numerical), where the knowledge could be events, relationships between objects, opinions, topics and anomaly time series, etc.
(2) To develop computational tools for visualising and representing the captured knowledge in an intuitive and easy to understand manner, which can empower end users to formulate decisions and convert data into actionable knowledge.
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 Computer Science, Mathematics, Engineering, Data Science or related disciplines. Good knowledge of Machine learning, statistical modelling and natural language processing. Some programming or software development experience would be beneficial.
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 C Lin ([email protected]) with a copy of your curriculum vitae and cover letter. All general enquiries should be directed to the Graduate School Admissions Unit ([email protected]).