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[½»Á÷] PhD positions at DERI at NUI Galway £¨Êý¾Ý´¦Àí£¬Çé¸Ð·ÖÎöÏà¹Ø£© ÒÑÓÐ1È˲ÎÓë

·ÖÏíÒ»¸öNUI GalwayµÄ²©Ê¿ÕÐÉúÐÅÏ¢£¬½ñÌì¸Õ·¢²¼µÄ£¬ÊÇ´ÓʦÐÖµÄÈËÈËÉÏ¿´À´µÄ¡£ÉêÇë½ØÖ¹ÈÕÆÚÊÇ7ÔÂ31ºÅ¡£ÓÐÐËȤµÄ³æÓÑ¿ÉÒÔÊÔÊÔ¹þ~
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We have a number of PhD positions funded by the new INSIGHT National Centre for Data Analytics. The positions will be based at  DERI at NUI Galway and will address the following area.

Real time analytics of social, semantic and linked data

The widespread use of the social web and mobile devices and the availability of large collaboratively-maintained, multi-domain knowledge sources such as Wikipedia and dbpedia have created the potential to consolidate and link data from several sources into enormous heterogeneous networked data sets consisting of nodes and edges with inherent semantic meaning, interdependence and provenance.

While graph analytics and processing frameworks generally consider generic edges and nodes, we plan to address the challenges in the analysis of large heterogeneous information networks ¨C influence measurement, information propagation, similarity calculation and clustering, structural role analysis, the detection of dependent concepts and latent relationships, real time analytics, the use and extraction of network schemas, and approaches for user-guided querying due to the additional complexity of the network space.

In parallel, we will address techniques to consolidate various sources of social semantic data, and to improve the quality of user-generated content through techniques such as gamification and the identification of authoritative users in crowdsourcing efforts.

The research will be applied in the following domains (amongst others)

Novel scientometrics based on analysis of social media and Web data
Real time social media analytics for large customer support centres
Real time recommendation of knowledge/related topics for media outlets with large archives
Social media analytics to identify influential users and their behaviours in the domain of digital media broadcasting

Some of the core challenges will be :

Novel approaches to  Social Network Analysis and Graph Mining on heterogeneous networks to uncover dependent concepts, labels, latent relationships and for causality exploration
Scalable and interpretable user/group role analysis and modelling
Graph-based real-time recommendation approaches using Linked Data as a source of open background data
Spatio-temporal correlation analysis on linking patterns to uncover root causes of changes to network structure
Predictive models of social network evolution and significant events such as churn, community formation
Stream-computing models for mining massive heterogeneous graphs  - for example graphs combining social and linked-data
Hybrid graph mining techniques combining statistical and logic, inductive and deductive approaches
Crawling, consolidation and indexing of social semantic data so that it can be exploited for large-scale real-time analytics
Evaluation and verification of crowd-sourced user-generated content

How to apply:

Applicants should have an excellent primary degree in computer science, maths or a relevant discipline (e.g. computationally focused social science). A master¡¯s degree would be a benefit. Applicants are asked to familiarise themselves with our previous research and to write a letter of introduction explaining their interest in the research we conduct and why they believe they are suitable for the position.

Each application should only contain a CV and the letter of introduction - please do not include references, testimonials, certificates, university grades etc. We may request these later.


Applications should be sent to conor.hayes@nuigalway.ie with the subject line INSIGHTSW3. The deadline for this application is July 31st, but potential applicants are encouraged to submit early.
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