Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/12660
DC FieldValueLanguage
dc.contributor.authorGregoriades, Andreas-
dc.contributor.authorChrystodoulides, Andreas-
dc.date.accessioned2018-08-20T06:44:08Z-
dc.date.available2018-08-20T06:44:08Z-
dc.date.issued2017-04-
dc.identifier.citation19th International Conference on Enterprise Information Systems, 2017, 26-29 Aprilen_US
dc.identifier.urihttps://hdl.handle.net/20.500.14279/12660-
dc.description.abstractTraffic accidents is the most common cause of injury among tourists. This paper presents a method and a tool for analysing historical traffic accident records using data mining techniques for the development of an application that warns tourist drivers of possible accident risks. The knowledge necessary for the specification of the application is based on patterns distilled from spatiotemporal analysis of historical accidents records. Raw accident obtained from Police records, underwent pre-processing and subsequently was integrated with secondary traffic-flow data from a mesoscopic simulation. Two data mining techniques were applied on the resulting dataset, namely, clustering with self-organizing maps (SOM) and association rules. The former was used to identify accident black spots, while the latter was applied in the clusters that emerged from SOM to identify causes of accidents in each black spot. Identified patterns were utilized to develop a software application to alert travellers of imminent accident risks, using characteristics of drivers along with real-time feeds of drivers' geolocation and environmental conditions.en_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.rights© 2017 SCITEPRESSen_US
dc.subjectAssociation rulesen_US
dc.subjectSelf-organizing mapsen_US
dc.subjectTourists safetyen_US
dc.titleTraffic accidents analysis using self-organizing maps and association rules for improved tourist safetyen_US
dc.typeConference Papersen_US
dc.collaborationCyprus University of Technologyen_US
dc.collaborationEuropean University Cyprusen_US
dc.subject.categoryComputer and Information Sciencesen_US
dc.countryCyprusen_US
dc.subject.fieldNatural Sciencesen_US
dc.publicationPeer Revieweden_US
cut.common.academicyear2016-2017en_US
item.fulltextNo Fulltext-
item.languageiso639-1en-
item.grantfulltextnone-
item.openairecristypehttp://purl.org/coar/resource_type/c_c94f-
item.cerifentitytypePublications-
item.openairetypeconferenceObject-
crisitem.author.deptDepartment of Communication and Marketing-
crisitem.author.facultyFaculty of Communication and Media Studies-
crisitem.author.orcid0000-0002-7422-1514-
crisitem.author.parentorgFaculty of Communication and Media Studies-
Appears in Collections:Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation
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