Previous work on moving object mobile group pattern mining defined and proposed algorithms for mobile group mining based on their individual movement data. Movement data is expected to be widely available owing to the increasing popularity of tractable mobile devices on the cutting edge. However, existing approaches of mobile group pattern mining do not consider temporal dimension. Considering that human beings often act as a group according to some temporal features such as routine activities, in this thesis, we engage in the discovery of valid mobile groups that pertain to the some temporal patterns. In our research, we introduce the calendar-based representation mechanism to be our representation of temporal dimension. Taking the calendar patterns into account, we define a new problem called calendar-based mobile group mining problem and develop efficient algorithms for the problem. The proposed algorithms are evaluated via synthetic location data generated by a sensible data generator.
| Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0721105-171155 |
| Date | 21 July 2005 |
| Creators | Chou, Yu-ping |
| Contributors | Chih-ping Wei, Fu-ren Lin, San-yih Hwang |
| Publisher | NSYSU |
| Source Sets | NSYSU Electronic Thesis and Dissertation Archive |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0721105-171155 |
| Rights | off_campus_withheld, Copyright information available at source archive |
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