Hdl Handle:
http://hdl.handle.net/10545/620890
Title:
Influence discovery in semantic networks: An initial approach
Authors:
Trovati, Marcello ( 0000-0001-6607-422X ) ; Bagdasar, Ovidiu ( 0000-0003-4193-9842 )
Abstract:
Assessing the influence between concepts, which include people, physical objects, as well as theoretical ideas, plays a crucial role in understanding and discovering knowledge. Despite the huge amount of literature on knowledge discovery in semantic networks, there has been little attempt to fully classify and investigate the influence, which also includes causality, of a semantic entity on another one as dynamical entities. In this paper we will introduce an approach to discover and assess influence among nodes in a semantic network, with the aim to provide a tool to identify its type and direction. Even though this is still being developed, the preliminary evaluation shows promising and interesting results.
Affiliation:
University of Derby
Citation:
Trovati, M. and Bagdasar, O. (2014), 'Influence discovery in semantic networks: An initial approach', Proceedings of the 16th International Conference on Computer Modelling and Simulation (UKSim), Emmanuel College, Cambridge University, Cambridge: UK, 26-28 March
Publisher:
IEEE
Journal:
Proceedings of the 16th International Conference on Computer Modelling and Simulation (UKSim)
Issue Date:
26-Mar-2014
URI:
http://hdl.handle.net/10545/620890
DOI:
10.1109/UKSim.2014.48
Additional Links:
http://ieeexplore.ieee.org/document/7046055/; http://uksim.info/uksim2014/uksim2014.htm; http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7045626
Type:
Meetings and Proceedings
Language:
en
ISBN:
9781479949229
Appears in Collections:
Department of Electronics, Computing & Maths

Full metadata record

DC FieldValue Language
dc.contributor.authorTrovati, Marcelloen
dc.contributor.authorBagdasar, Ovidiuen
dc.date.accessioned2016-11-17T12:30:06Z-
dc.date.available2016-11-17T12:30:06Z-
dc.date.issued2014-03-26-
dc.identifier.citationTrovati, M. and Bagdasar, O. (2014), 'Influence discovery in semantic networks: An initial approach', Proceedings of the 16th International Conference on Computer Modelling and Simulation (UKSim), Emmanuel College, Cambridge University, Cambridge: UK, 26-28 Marchen
dc.identifier.isbn9781479949229-
dc.identifier.doi10.1109/UKSim.2014.48-
dc.identifier.urihttp://hdl.handle.net/10545/620890-
dc.description.abstractAssessing the influence between concepts, which include people, physical objects, as well as theoretical ideas, plays a crucial role in understanding and discovering knowledge. Despite the huge amount of literature on knowledge discovery in semantic networks, there has been little attempt to fully classify and investigate the influence, which also includes causality, of a semantic entity on another one as dynamical entities. In this paper we will introduce an approach to discover and assess influence among nodes in a semantic network, with the aim to provide a tool to identify its type and direction. Even though this is still being developed, the preliminary evaluation shows promising and interesting results.en
dc.language.isoenen
dc.publisherIEEEen
dc.relation.urlhttp://ieeexplore.ieee.org/document/7046055/en
dc.relation.urlhttp://uksim.info/uksim2014/uksim2014.htmen
dc.relation.urlhttp://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7045626en
dc.subjectSemanticsen
dc.subjectMathematical modelen
dc.subjectSocial networking sitesen
dc.subjectComputational modelingen
dc.titleInfluence discovery in semantic networks: An initial approachen
dc.typeMeetings and Proceedingsen
dc.contributor.departmentUniversity of Derbyen
dc.identifier.journalProceedings of the 16th International Conference on Computer Modelling and Simulation (UKSim)en
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