Eurizon.eu

Organization: University of Sheffield - Department of Computer Science

Location: Sheffield, UK

Field: Computer Science

Requirements:

Candidates should have a First Class Honours or a good 2.1 degree in Computer Science or Mathematics and have excellent computer programming skills. Experience with machine learning techniques for natural language processing is essential, and detailed knowledge of text summarisation and/or user modelling would be highly desirable. Research experience with Facebook, Twitter, and other social media would also be desirable, but is not strictly necessary, as would be knowledge of GATE.

Abstract:

The aim of this studentship is to design machine learning methods to better capture information about the user from their social media activities and then use that information to summarise relevant new social media content.

Description:

The aim of this studentship is to design machine learning methods to better capture information about the user from their social media activities and then use that information to summarise relevant new social media content. This research topic falls in the broader area of Natural Language Processing (NLP), where Sheffield University has established an internationally-leading reputation. In particular, through their widely-used GATE NLP toolkit (http://gate.ac.uk) which provides many indispensable tools for working with large unstructured text collections, including semantic search, information extraction and translation. The studentship will be associated with Dr. Bontcheva's EPSRC-funded career acceleration fellowship, details on which can be found at http://www.dcs.shef.ac.uk/~kalina/caf.html

Deadline: 04-03-2011

Contacts:

Link: http://www.shef.ac.uk/postgraduate/research/apply

Email: K.Bontcheva@dcs.shef.ac.uk

Email: tcohn@dcs.shef.ac.uk

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