{"title":"移动软件生态系统中一种高效的应用设备匹配方法","authors":"Heuijin Lee, Sungwon Kang, Myung-Gyun Kim","doi":"10.1109/APSEC.2014.36","DOIUrl":null,"url":null,"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.","PeriodicalId":380881,"journal":{"name":"2014 21st Asia-Pacific Software Engineering Conference","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"An Efficient Application-Device Matching Method for the Mobile Software Ecosystem\",\"authors\":\"Heuijin Lee, Sungwon Kang, Myung-Gyun Kim\",\"doi\":\"10.1109/APSEC.2014.36\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":380881,\"journal\":{\"name\":\"2014 21st Asia-Pacific Software Engineering Conference\",\"volume\":\"32 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 21st Asia-Pacific Software Engineering Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/APSEC.2014.36\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 21st Asia-Pacific Software Engineering Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APSEC.2014.36","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Efficient Application-Device Matching Method for the Mobile Software Ecosystem
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.