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Conference Paper: Geo-social skyline queries

TitleGeo-social skyline queries
Authors
KeywordsEngineering controlled terms
Database systems
Indexing (of information)
Mobile devices
Query processing
Social networking (online)
Issue Date2014
PublisherSpringer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/
Citation
The 19th International Conference on Database Systems for Advanced Applications (DASFAA 2014), Bali, Indonesia, 21-24 April 2014. In Lecture Notes in Computer Science, 2014, v. 8422, p. 77-91 How to Cite?
AbstractBy leveraging the capabilities of modern GPS-equipped mobile devices providing social-networking services, the interest in developing advanced services that combine location-based services with social networking services is growing drastically. Based on geo-social networks that couple personal location information with personal social context information, such services are facilitated by geo-social queriesthat extract useful information combining social relationships and current locations of the users. In this paper, we tackle the problem of geo-social skyline queries, a problem that has not been addressed so far. Given a set of persons D connected in a social network SN with information about their current location, a geo-social skyline query reports for a given user U ε D and a given location P (not necessarily the location of the user) the pareto-optimal set of persons who are close to P and closely connected to U in SN. We measure the social connectivity between users using the widely adoted, but very expensive Random Walk with Restart method (RWR) to obtain the social distance between users in the social network. We propose an efficient solution by showing how the RWR-distance can be bounded efficiently and effectively in order to identify true hits and true drops early. Our experimental evaluation shows that our presented pruning techniques allow to vastly reduce the number of objects for which a more exact social distance has to be computed, by using our proposed bounds only. © 2014 Springer International Publishing Switzerland.
Persistent Identifierhttp://hdl.handle.net/10722/199308
ISBN
ISSN
2005 Impact Factor: 0.402
2015 SCImago Journal Rankings: 0.252

 

DC FieldValueLanguage
dc.contributor.authorEmrich, Ten_US
dc.contributor.authorFranzke, MHen_US
dc.contributor.authorMamoulis, Nen_US
dc.contributor.authorRenz, Men_US
dc.contributor.authorZuefle, Aen_US
dc.date.accessioned2014-07-22T01:13:04Z-
dc.date.available2014-07-22T01:13:04Z-
dc.date.issued2014en_US
dc.identifier.citationThe 19th International Conference on Database Systems for Advanced Applications (DASFAA 2014), Bali, Indonesia, 21-24 April 2014. In Lecture Notes in Computer Science, 2014, v. 8422, p. 77-91en_US
dc.identifier.isbn978-3-319-05812-2-
dc.identifier.issn0302-9743en_US
dc.identifier.urihttp://hdl.handle.net/10722/199308-
dc.description.abstractBy leveraging the capabilities of modern GPS-equipped mobile devices providing social-networking services, the interest in developing advanced services that combine location-based services with social networking services is growing drastically. Based on geo-social networks that couple personal location information with personal social context information, such services are facilitated by geo-social queriesthat extract useful information combining social relationships and current locations of the users. In this paper, we tackle the problem of geo-social skyline queries, a problem that has not been addressed so far. Given a set of persons D connected in a social network SN with information about their current location, a geo-social skyline query reports for a given user U ε D and a given location P (not necessarily the location of the user) the pareto-optimal set of persons who are close to P and closely connected to U in SN. We measure the social connectivity between users using the widely adoted, but very expensive Random Walk with Restart method (RWR) to obtain the social distance between users in the social network. We propose an efficient solution by showing how the RWR-distance can be bounded efficiently and effectively in order to identify true hits and true drops early. Our experimental evaluation shows that our presented pruning techniques allow to vastly reduce the number of objects for which a more exact social distance has to be computed, by using our proposed bounds only. © 2014 Springer International Publishing Switzerland.en_US
dc.languageengen_US
dc.publisherSpringer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/en_US
dc.relation.ispartofLecture Notes in Computer Scienceen_US
dc.rightsThe original publication is available at www.springerlink.comen_US
dc.subjectEngineering controlled termsen_US
dc.subjectDatabase systemsen_US
dc.subjectIndexing (of information)en_US
dc.subjectMobile devicesen_US
dc.subjectQuery processingen_US
dc.subjectSocial networking (online)-
dc.titleGeo-social skyline queriesen_US
dc.typeConference_Paperen_US
dc.identifier.emailMamoulis, N: nikos@cs.hku.hken_US
dc.identifier.authorityMamoulis, N=rp00155en_US
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1007/978-3-319-05813-9_6en_US
dc.identifier.scopuseid_2-s2.0-84900299190-
dc.identifier.hkuros230460en_US
dc.identifier.volume8422en_US
dc.identifier.spage77en_US
dc.identifier.epage91en_US
dc.publisher.placeGermanyen_US
dc.customcontrol.immutablesml 140730-

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