A data mining approach for location prediction in mobile environments
buir.contributor.author | Ulusoy, Özgür | |
dc.citation.epage | 146 | en_US |
dc.citation.issueNumber | 2 | en_US |
dc.citation.spage | 121 | en_US |
dc.citation.volumeNumber | 54 | en_US |
dc.contributor.author | Yavaş G. | en_US |
dc.contributor.author | Katsaros, D. | en_US |
dc.contributor.author | Ulusoy, Özgür | en_US |
dc.contributor.author | Manolopoulos, Y. | en_US |
dc.date.accessioned | 2016-02-08T10:22:49Z | |
dc.date.available | 2016-02-08T10:22:49Z | en_US |
dc.date.issued | 2005 | en_US |
dc.department | Department of Computer Engineering | en_US |
dc.description.abstract | Mobility prediction is one of the most essential issues that need to be explored for mobility management in mobile computing systems. In this paper, we propose a new algorithm for predicting the next inter-cell movement of a mobile user in a Personal Communication Systems network. In the first phase of our three-phase algorithm, user mobility patterns are mined from the history of mobile user trajectories. In the second phase, mobility rules are extracted from these patterns, and in the last phase, mobility predictions are accomplished by using these rules. The performance of the proposed algorithm is evaluated through simulation as compared to two other prediction methods. The performance results obtained in terms of Precision and Recall indicate that our method can make more accurate predictions than the other methods. © 2004 Elsevier B.V. All rights reserved. | en_US |
dc.description.provenance | Made available in DSpace on 2016-02-08T10:22:49Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 2005 | en_US |
dc.identifier.doi | 10.1016/j.datak.2004.09.004 | en_US |
dc.identifier.issn | 1872-6933 | en_US |
dc.identifier.issn | 0169-023X | en_US |
dc.identifier.uri | http://hdl.handle.net/11693/24015 | en_US |
dc.language.iso | English | en_US |
dc.publisher | Elsevier | en_US |
dc.relation.isversionof | http://dx.doi.org/10.1016/j.datak.2004.09.004 | en_US |
dc.source.title | Data and Knowledge Engineering | en_US |
dc.subject | Data mining | en_US |
dc.subject | Location prediction | en_US |
dc.subject | Mobile computing | en_US |
dc.subject | Mobility patterns | en_US |
dc.subject | Mobility prediction | en_US |
dc.subject | Algorithms | en_US |
dc.subject | Data mining | en_US |
dc.subject | Data processing | en_US |
dc.subject | Global positioning system | en_US |
dc.subject | Knowledge engineering | en_US |
dc.subject | Personal communication systems | en_US |
dc.subject | Probability | en_US |
dc.subject | Resource allocation | en_US |
dc.subject | Location prediction | en_US |
dc.subject | Mobile user trajectories | en_US |
dc.subject | Mobility patterns | en_US |
dc.subject | Mobility predictions | en_US |
dc.subject | Mobile computing | en_US |
dc.title | A data mining approach for location prediction in mobile environments | en_US |
dc.type | Article | en_US |
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