DC Field | Value | Language |
---|---|---|
dc.contributor.author | Anagnostopoulos, Theodoros | - |
dc.contributor.author | Anagnostopoulos, Christos | - |
dc.contributor.author | Hadjiefthymiades, Stathes | - |
dc.date.accessioned | 2024-07-09T13:04:51Z | - |
dc.date.available | 2024-07-09T13:04:51Z | - |
dc.date.issued | 2011-11-29 | - |
dc.identifier | scopus-82055172253 | - |
dc.identifier.isbn | 978-0-7695-4436-6 | - |
dc.identifier.isbn | 978-1-4577-0581-6 | - |
dc.identifier.issn | 1551-6245 | - |
dc.identifier.other | 82055172253 | - |
dc.identifier.uri | https://uniwacris.uniwa.gr/handle/3000/2699 | - |
dc.description.abstract | Mobile applications are required to operate in highly dynamic pervasive computing environments of dynamic nature and predict the location of mobile users in order to act proactively. We focus on the location prediction and propose a new model/framework. Our model is used for the classification of the spatial trajectories through the adoption of Machine Learning (ML) techniques. Predicting location is treated as a classification problem through supervised learning. We perform the performance assessment of our model through synthetic and real-world data. We monitor the important metrics of prediction accuracy and training sample size. | en_US |
dc.language.iso | en | en_US |
dc.relation.ispartof | Proceedings of the 12th IEEE International Conference on Mobile Data Management (IEEE MDM 2011) | en_US |
dc.subject | location prediction | en_US |
dc.subject | Location representation | en_US |
dc.subject | Machine learning | en_US |
dc.subject | Trajectory classification | en_US |
dc.title | Mobility prediction based on machine learning | en_US |
dc.type | Conference Paper | en_US |
dc.relation.conference | 12th IEEE International Conference on Mobile Data Management (IEEE MDM 2011), 06-09 June 2011, Lulea, Sweden | en_US |
dc.identifier.doi | 10.1109/MDM.2011.60 | en_US |
dc.identifier.scopus | 2-s2.0-82055172253 | - |
dcterms.accessRights | 0 | en_US |
dc.relation.dept | Department of Business Administration | en_US |
dc.relation.faculty | School of Administrative, Economics and Social Sciences | en_US |
dc.relation.volume | 2 | en_US |
dc.identifier.spage | 27 | en_US |
dc.identifier.epage | 30 | en_US |
dc.collaboration | University of West Attica (UNIWA) | en_US |
dc.subject.field | Engineering and Technology | en_US |
dc.journals | Open Access | en_US |
dc.publication | Peer Reviewed | en_US |
dc.country | Greece | en_US |
local.metadatastatus | not verified | en_US |
item.openairetype | Conference Paper | - |
item.grantfulltext | none | - |
item.fulltext | No Fulltext | - |
item.cerifentitytype | Publications | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.languageiso639-1 | en | - |
crisitem.author.dept | Department of Business Administration | - |
crisitem.author.faculty | School of Administrative, Economics and Social Sciences | - |
crisitem.author.orcid | 0000-0002-5587-2848 | - |
crisitem.author.parentorg | School of Administrative, Economics and Social Sciences | - |
Appears in Collections: | Book Chapter / Κεφάλαιο Βιβλίου |
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