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dc.contributor.authorDokuz A.S.
dc.contributor.authorCelik M.
dc.date.accessioned2019-08-01T13:38:39Z
dc.date.available2019-08-01T13:38:39Z
dc.date.issued2017
dc.identifier.issn2194-9042
dc.identifier.urihttps://dx.doi.org/10.5194/isprs-annals-IV-4-W4-197-2017
dc.identifier.urihttps://hdl.handle.net/11480/1769
dc.description4th International GeoAdvances Workshop - GeoAdvances 2017: ISPRS Workshop on Multi-Dimensional and Multi-Scale Spatial Data Modeling -- 14 October 2017 through 15 October 2017 -- -- 131995en_US
dc.description.abstractSocially important locations are places which are frequently visited by social media users in their social media lifetime. Discovering socially important locations provide several valuable information about user behaviours on social media networking sites. However, discovering socially important locations are challenging due to data volume and dimensions, spatial and temporal calculations, location sparseness in social media datasets, and inefficiency of current algorithms. In the literature, several studies are conducted to discover important locations, however, the proposed approaches do not work in computationally efficient manner. In this study, we propose Fast SS-ILM algorithm by modifying the algorithm of SS-ILM to mine socially important locations efficiently. Experimental results show that proposed Fast SS-ILM algorithm decreases execution time of socially important locations discovery process up to 20 %. © Authors 2017.en_US
dc.description.sponsorshipThis research was supported by the Research Fund of Erciyes University, Project Number: FDK-2017-7233.en_US
dc.language.isoengen_US
dc.publisherCopernicus GmbHen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectdata miningen_US
dc.subjectsocial important locations miningen_US
dc.subjectspatial social media miningen_US
dc.subjectTwitteren_US
dc.titleFAST SS-ILM: A COMPUTATIONALLY EFFICIENT ALGORITHM to DISCOVER SOCIALLY IMPORTANT LOCATIONSen_US
dc.typeconferenceObjecten_US
dc.relation.journalISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciencesen_US
dc.departmentNiğde ÖHÜen_US
dc.identifier.volume4en_US
dc.identifier.issue4W4en_US
dc.identifier.startpage197en_US
dc.identifier.endpage202en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.contributor.institutionauthor[0-Belirlenecek]
dc.identifier.doi10.5194/isprs-annals-IV-4-W4-197-2017


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