We have a number of PhD positions funded by the new INSIGHT National
Centre for Data Analytics <http://www.insight-centre.org/>. The
positions will be based at DERI <http://deri.ie/> 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 ? 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.
For more information, please visit <http://uimr.deri.ie/vacancies/>
- --
Dr. Marcel Karnstedt <http://www.marcel.karnstedt.com/>
phone: +353 91 494034
Digital Enterprise Research Institute (DERI) <http://www.deri.ie/>
Unit for Information Mining and Retrieval (UIMR) <http://uimr.deri.ie/>
National University of Ireland, Galway (NUIG) <http://www.nuigalway.ie/>
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Centre for Data Analytics <http://www.insight-centre.org/>. The
positions will be based at DERI <http://deri.ie/> 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 ? 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.
For more information, please visit <http://uimr.deri.ie/vacancies/>
- --
Dr. Marcel Karnstedt <http://www.marcel.karnstedt.com/>
phone: +353 91 494034
Digital Enterprise Research Institute (DERI) <http://www.deri.ie/>
Unit for Information Mining and Retrieval (UIMR) <http://uimr.deri.ie/>
National University of Ireland, Galway (NUIG) <http://www.nuigalway.ie/>
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