Logo des Repositoriums
 

Efficient interest group discovery in social networks using an integrated structure/quality index

dc.contributor.authorBudura, Adriana
dc.contributor.authorMichel , Sebastian
dc.contributor.authorAberer, Karl
dc.contributor.editorHärder, Theo
dc.contributor.editorLehner, Wolfgang
dc.contributor.editorMitschang, Bernhard
dc.contributor.editorSchöning, Harald
dc.contributor.editorSchwarz, Holger
dc.date.accessioned2019-01-17T10:36:45Z
dc.date.available2019-01-17T10:36:45Z
dc.date.issued2011
dc.description.abstractWe consider the problems of interest group discovery in a social network graph using term-based topic descriptions. For a given query consisting of a set of terms, we efficiently compute a connected subset of users that jointly cover the query terms, based on the annotation vocabulary utilized by users in the past. The presented approach is twofold; first we identify so-called seed users, centers of interest groups, that act as starting points of the group exploration. Subsequently, we inspect the seed users' neighborhoods and build up the tree connecting the most promising neighbors. We demonstrate the applicability and efficiency of our method by conducting a series of experiments on data extracted from a Web portal showing that our method does not only provide accurate answers but calculates these also in an efficient way.en
dc.identifier.isbn978-3-88579-274-1
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/19589
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofDatenbanksysteme für Business, Technologie und Web (BTW)
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-180
dc.titleEfficient interest group discovery in social networks using an integrated structure/quality indexen
dc.typeText/Conference Paper
gi.citation.endPage378
gi.citation.publisherPlaceBonn
gi.citation.startPage367
gi.conference.date02.-04.03.2011
gi.conference.locationKaiserslautern
gi.conference.sessiontitleRegular Research Papers

Dateien

Originalbündel
1 - 1 von 1
Vorschaubild nicht verfügbar
Name:
367.pdf
Größe:
166.42 KB
Format:
Adobe Portable Document Format