期刊論文
| 學年 | 105 |
|---|---|
| 學期 | 1 |
| 出版（發表）日期 | 2016-12-01 |
| 作品名稱 | A cloud-based system for dynamically capturing appliance usage relations |
| 作品名稱（其他語言） | |
| 著者 | Yi-Cheng Chen; Shih-Hao Chang; Wei-Hsun Liao; Jianquan Liu; Yutaka Watanobe |
| 單位 | |
| 出版者 | |
| 著錄名稱、卷期、頁數 | International Journal of Web and Gird Services 12(3), p.257-272 |
| 摘要 | Nowadays, owing to the great advent of sensor technology, data can be collected easily. Mining Internet of Things IoT data has attracted researchers' attention owing to its practicability. Mining smart home data is one significant application in the IoT domain. Generally, the usage data of appliances in a smart environment are generated progressively; visualising how appliances are used from huge amount of data is a challenging issue. Hence, an algorithm is needed to dynamically discover appliance usage patterns. Prior studies on usage pattern discovery are mainly focused on discovering patterns while ignoring the dynamic maintenance of mined results. In this paper, a cloud-based system, Dynamic Correlation Mining System DCMS, is developed to incrementally capture the usage correlations among appliances in a smart home environment. Furthermore, several pruning strategies are proposed to effectively reduce the search space. Experimental results indicate that the developed system is efficient in execution time and possesses great scalability. Subsequent application of DCMS on a real data set also demonstrates the practicability of mining smart home data. |
| 關鍵字 | incremental mining;usage relations;sequential patterns;smart homes;cloud computing;appliance usage patterns;data mining;internet of things;IoT;smart home data;home appliances |
| 語言 | en |
| ISSN | 1741-1114;1741-1106 |
| 期刊性質 | 國外 |
| 收錄於 | SCI EI |
| 產學合作 | |
| 通訊作者 | |
| 審稿制度 | 是 |
| 國別 | GBR |
| 公開徵稿 | |
| 出版型式 | ,電子版,紙本 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/108678 ) |