Name
Abstract | ||
|---|---|---|
In the mobile software ecosystem, a method that finds out the applications that are compatible with the device of an end user is called application-device matching. In the current mobile software environment, the device fragmentation causes substantial degree of inaccuracy in matching applications with devices as the traditional platform-centric method handles only the features of platform vendors without considering the unique feature set of a certain device, such as device-manufacturer's features, resulting in a low accuracy in matching applications and devices. This paper proposes a new matching method that is device-centric, which achieves high accuracy in application-device matching by grouping features of existing devices and then using it as criteria of application-device matching. To demonstrate the performance of our method, we conduct a case study with 22 devices and 10 applications in the Google Android mobile software ecosystem. The result of case study shows our proposed method shows a higher accuracy. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/APSEC.2014.36 | APSEC (1) |
Keywords | Field | DocType |
matching method,software ecosystem,mobile software ecosystem,android,mobile computing,android (operating system),google android mobile software ecosystem,application-device matching method,device fragmentation,feature extraction,mobile communication,global positioning system | Mobile computing,Mobile search,Android (operating system),Computer science,Mobile station,Real-time computing,Software,Market fragmentation,Mobile telephony,Software ecosystem | Conference |
Volume | ISSN | Citations |
1 | 1530-1362 | 3 |
PageRank | References | Authors |
0.41 | 6 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Heuijin Lee | 1 | 5 | 0.78 |
| Sungwon Kang | 2 | 404 | 49.55 |
| Myung-Chul Kim | 3 | 665 | 57.05 |