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[PhD studentship] Knowledge Capturing and Exploitation in Social Big Data

From: Jeff Pan <jeffpan.sw@googlemail.com>
Date: Tue, 13 May 2014 18:07:41 +0100
Message-ID: <CAC9TgjjeUU6uPtvEKUv42LPj5D-m16pVFy=EcZa5D--wviwzPg@mail.gmail.com>
To: public-vocabs@w3.org
*** Apologies for cross posting. ***

PhD Research Project - Possible Funding for a Highly Qualified Student
Knowledge Capturing and Exploitation in Social Big Data
University of Aberdeen

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.

For further details:
http://qr.net/y2zk

Jeff Z. Pan:
http://homepages.abdn.ac.uk/jeff.z.pan/pages/

Chenghua Lin:
http://www.abdn.ac.uk/ncs/people/profiles/chenghua.lin
Received on Tuesday, 13 May 2014 17:08:08 UTC

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