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dc.contributor.authorJaber, M
dc.contributor.authorPapapetrou, P
dc.contributor.authorHelmer, S
dc.contributor.authorWood, PT
dc.date.accessioned2015-06-11T15:04:12Z
dc.date.available2015-06-11T15:04:12Z
dc.date.issued2014
dc.identifier.isbn978-3-319-12570-1
dc.identifier.urihttp://hdl.handle.net/10863/526
dc.description.abstractWe study the problem of detecting hierarchical ties in a social network by exploiting the interaction patterns between the actors (members) involved in the network. Motivated by earlier work using a rank-based approach, i.e., Rooted-PageRank, we introduce a novel time-sensitive method, called T-RPR, that captures and exploits the dynamics and evolution of the interaction patterns in the network in order to identify the underlying hierarchical ties. Experiments on two real datasets demonstrate the performance of T-RPR in terms of recall and show its superiority over a recent competitor method.en_US
dc.publisherSpringeren_US
dc.relation.ispartofseriesLecture Notes in Computer Science;
dc.titleUsing Time-Sensitive Rooted PageRank to Detect Hierarchical Social Relationshipsen_US
dc.typeBook chapteren_US
dc.date.updated2015-05-20T07:47:21Z
dc.publication.titleAdvances in Intelligent Data Analysis XIII: 13th International Symposium, IDA 2014, Leuven, Belgium, October 30 -- November 1, 2014. Proceedings
dc.language.isiEN-GB
dc.description.fulltextinternalen_US


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