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| Content Provider | Springer Nature Link |
|---|---|
| Author | Iwan, Lukman Hakim Safar, Maytham |
| Copyright Year | 2010 |
| Abstract | With the rapid progress of mobile technology, an increasing number of mobile devices are able to be tracked. In the field of cellular technology, we can track the location of a mobile phone user by locating the cell connected with his/her mobile phone. When a mobile user moves from one location to another, we can track his/her mobile device connecting from one cell to another cell. This work focuses on mining patterns from mobile user movement data. Two new algorithms are proposed, namely: location link and user link pattern mining algorithms. Both proposed algorithms are able to mine a pattern from another pattern instead of mining a pattern directly from a data source. Therefore, the pattern will be more concise and the processing time of both algorithms will be faster. Both algorithms have been evaluated from two perspectives: pattern mining generation and time processing. The experiment results from the processing time aspect indicate that larger datasets and lower values of user-defined thresholds lead to a longer processing time for both algorithms. Furthermore, the processing time of both proposed algorithms are dominated by the preparation process. |
| Starting Page | 295 |
| Ending Page | 308 |
| Page Count | 14 |
| File Format | |
| ISSN | 18685137 |
| Journal | Journal of Ambient Intelligence and Humanized Computing |
| Volume Number | 1 |
| Issue Number | 4 |
| e-ISSN | 18685145 |
| Language | English |
| Publisher | Springer-Verlag |
| Publisher Date | 2010-07-01 |
| Publisher Place | Berlin, Heidelberg |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | User Interfaces and Human Computer Interaction Robotics and Automation Artificial Intelligence (incl. Robotics) Computational Intelligence |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Science |
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