| 000 | 02656cam a2200337 a 4500 | ||
|---|---|---|---|
| 003 | EG-GiCUC | ||
| 005 | 20250223032922.0 | ||
| 008 | 220222s2022 ua d f m 000 0 eng d | ||
| 040 |
_aEG-GiCUC _beng _cEG-GiCUC |
||
| 041 | 0 | _aeng | |
| 049 | _aDeposite | ||
| 097 | _aPh.D | ||
| 099 | _aCai01.20.04.Ph.D.2022.Em.M | ||
| 100 | 0 | _aEman Omar Eldawy | |
| 245 | 1 | 0 |
_aManagement and mining of big spatiotemporal data / _cEman Omar Eldawy ; Supervised Hoda Mokhtar Omar Mokhtar |
| 246 | 1 | 5 | _aإدارة وتنقيب البيانات المكانية الزمانية الكبيرة |
| 260 |
_aCairo : _bEman Omar Eldawy , _c2022 |
||
| 300 |
_a73 P. : _bcharts ; _c30cm |
||
| 502 | _aThesis (Ph.D.) - Cairo University - Faculty of Computers and Artificial Intelligence - Department of Information System | ||
| 520 | _aThe fast advancement that we are witnessing today in mobile computing techniques has generated massive spatiotemporal data. Mining spatiotemporal data and especially outlier detection in trajectory data is a crucial and challenging topic as it can be used in a wide range of applications, including transportation management, public safety, urban planning, and environment monitoring. An outlier (anomaly) trajectory is a trajectory that has different characteristics than normal trajectories. In our research, we present the CB-TOD algorithm to detect outlier sub-trajectories and outlier trajectories by utilizing a clustering-based methodology. In the CB-TOD algorithm, the computational time is reduced decreasing the size of the trajectories dataset and representing each trajectory with the summary set of line segments that are sufficient to define the trajectory behavior without missing the basic motion information. After that, similar line segments based on the distance are grouped into a cluster. After clustering, for each trajectory, we distinguish the cluster that has the smallest number of segments and neighbors.This cluster is marked as an outlier cluster for this trajectory and accordingly, the line segments included in this detected cluster are classified as outlier segments. Moreover, a trajectory that contains a considerable number of outlying partitions is identified as an outlier trajectory | ||
| 530 | _aIssued also as CD | ||
| 650 | 0 | _aSpatioTemporalitym | |
| 653 | 4 | _aClustering-Based Trajectory Outlier Detection (CB-TOD) | |
| 653 | 4 | _aMining of big spatiotemporal data | |
| 653 | 4 | _aSpatiotemporal | |
| 700 | 0 |
_aHoda Mokhtar Omar Mokhtar , _eSupervisor |
|
| 856 | _uhttp://172.23.153.220/th.pdf | ||
| 905 |
_aNazla _eRevisor |
||
| 905 |
_aShimaa _eCataloger |
||
| 942 |
_2ddc _cTH |
||
| 999 |
_c84303 _d84303 |
||