Algorithms for Mining Human Spatial-Temporal Behavior Pattern from Mobile Phone Trajectories
| Autor: | Chen-lu Wang, Yi-bo Zhu, Pei-ming Bao, Gen-lin Ji |
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| Rok vydání: | 2017 |
| Předmět: |
Focus (computing)
010504 meteorology & atmospheric sciences Social network business.industry Computer science Big data 0211 other engineering and technologies Parallel algorithm Behavioral pattern 02 engineering and technology 01 natural sciences Mobile phone Smart city Smart card business Algorithm 021101 geological & geomatics engineering 0105 earth and related environmental sciences |
| Zdroj: | DEStech Transactions on Computer Science and Engineering. |
| ISSN: | 2475-8841 |
| DOI: | 10.12783/dtcse/cst2017/12582 |
| Popis: | The research on human spatial-temporal behavior has always been the focus of urban geographic studies. In today’s society, social networks, smart phones and smart cards can provide massive data for researchers to analysis human behavior. From mobile phone trajectories, this paper presents algorithms for mining human spatial-temporal behavior pattern, which includes not only the regular movement pattern of individuals, but also the co-occurrence pattern among user groups. The parallel algorithms in this paper are proposed for big data of user trajectories, and the experimental results show that the proposed algorithms are effective. The research on human spatial-temporal behavior pattern can be applied to urban spatial-temporal behavior analysis, smart city construction and other areas. |
| Databáze: | OpenAIRE |
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