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Conference Paper: GPS-based location extraction and presence management for mobile instant messenger

TitleGPS-based location extraction and presence management for mobile instant messenger
Authors
Issue Date2007
PublisherSpringer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/
Citation
The 2007 IFIP International Conference on Embedded and Ubiquitous Computing (EUC 2007), Taipei, Taiwan, 17-20 December 2007. In Lecture Notes In Computer Science, 2007, v. 4808, p. 309-320 How to Cite?
AbstractLocation is the most essential presence information for mobile users. In this paper, we present an improved time-based clustering technique for extracting significant locations from GPS data stream. This new location extraction mechanism is incorporated with Google Maps for realizing cooperative place annotation on mobile instant messengers (MIM). To enhance the context-awareness of the MIM system, we further develop an ontology-based presence model for inferring the location clues of IM buddies. The GPS-based location extraction algorithm has been implemented on a Smartphone and evaluated using a real-life GPS trace. We show that the proposed clustering algorithm can achieve more accurate results as it considers the time interval of intermittent location revisits. The incorporation of location information with the high-level contexts, such as mobile user's current activity and their social relationship, can achieve more responsive and accurate presence update. © IFIP International Federation for Information Processing 2007.
Persistent Identifierhttp://hdl.handle.net/10722/93027
ISSN
2005 Impact Factor: 0.402
2015 SCImago Journal Rankings: 0.252
References

 

DC FieldValueLanguage
dc.contributor.authorHu, Hen_HK
dc.contributor.authorWang, CLen_HK
dc.date.accessioned2010-09-25T14:48:40Z-
dc.date.available2010-09-25T14:48:40Z-
dc.date.issued2007en_HK
dc.identifier.citationThe 2007 IFIP International Conference on Embedded and Ubiquitous Computing (EUC 2007), Taipei, Taiwan, 17-20 December 2007. In Lecture Notes In Computer Science, 2007, v. 4808, p. 309-320en_HK
dc.identifier.issn0302-9743-
dc.identifier.urihttp://hdl.handle.net/10722/93027-
dc.description.abstractLocation is the most essential presence information for mobile users. In this paper, we present an improved time-based clustering technique for extracting significant locations from GPS data stream. This new location extraction mechanism is incorporated with Google Maps for realizing cooperative place annotation on mobile instant messengers (MIM). To enhance the context-awareness of the MIM system, we further develop an ontology-based presence model for inferring the location clues of IM buddies. The GPS-based location extraction algorithm has been implemented on a Smartphone and evaluated using a real-life GPS trace. We show that the proposed clustering algorithm can achieve more accurate results as it considers the time interval of intermittent location revisits. The incorporation of location information with the high-level contexts, such as mobile user's current activity and their social relationship, can achieve more responsive and accurate presence update. © IFIP International Federation for Information Processing 2007.-
dc.languageengen_HK
dc.publisherSpringer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/en_HK
dc.relation.ispartofLecture Notes in Computer Scienceen_HK
dc.titleGPS-based location extraction and presence management for mobile instant messengeren_HK
dc.typeConference_Paperen_HK
dc.identifier.emailWang, CL: clwang@cs.hku.hken_HK
dc.identifier.authorityWang, CL=rp00183en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.scopuseid_2-s2.0-38149001570-
dc.identifier.hkuros149516en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-38149001570&selection=ref&src=s&origin=recordpage-
dc.identifier.volume4808-
dc.identifier.spage309en_HK
dc.identifier.epage320en_HK
dc.publisher.placeGermany-
dc.identifier.scopusauthoridHu, DH=23396949100-
dc.identifier.scopusauthoridWang, CL=7501646188-
dc.customcontrol.immutablesml 160111 - merged-

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