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| 一种面向移动应用的探索式服务组合方法 |
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白琳1,2,3, 魏峻1,2, 黄翔4, 叶丹1,2, 黄涛1,2
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1.中国科学院 软件研究所 软件工程技术中心, 北京 100190;2.计算机科学国家重点实验室(中国科学院 软件研究所), 北京 100190;3.中国科学院大学, 北京 100190;4.中国能源建设集团 广东省电力设计研究院, 广东 广州 510663
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| 摘要: |
| 开放移动平台的涌现,加速了服务组合技术在移动应用开发过程中的应用和发展.当前的移动应用开发大多采用静态的服务分类聚集的组合方式,很容易引起功能过载和服务访问链过长的问题,严重影响了移动应用的易用性.针对这一问题,结合移动应用领域的特点,提出一种探索式服务组合方法.该方法通过感知上下文变化为用户构造当前环境下可用的服务集合,并通过交互将用户选择的服务即时地组合到应用中.基于上下文构造可组合的候选服务集合是其中一个核心技术,采用历史挖掘的算法,利用用户在不同上下文环境下选择服务的历史记录,挖掘出上下文与服务间的关联关系,以此作为匹配候选服务的依据.在关联规则挖掘方面,对传统的FP-tree算法进行了扩展,使其支持移动应用领域中二维数据项的挖掘.实验结果表明,扩展后的算法比传统算法在服务匹配方面具有更高的准确率和命中率. |
| 关键词: 探索式服务组合 上下文感知 移动应用 关联规则 FP-tree |
| DOI：10.13328/j.cnki.jos.004607 |
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| 基金项目:国家自然科学基金(61170074, 61173005); 国家科技支撑计划(2012BAH14B02); 国家高技术研究发展计划(863)(2012AA011204) |
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| An Exploratory Service Composition Approach for Mobile Application |
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BAI Lin1,2,3, WEI Jun1,2, HUANG Xiang4, YE Dan1,2, HUANG Tao1,2
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1.Technology Center of Software Engineering, Institute of Software, The Chinese Academy of Sciences, Beijing 100190, China;2.State Key Laboratory of Computer Science (Institute of Software, The Chinese Academy of Sciences), Beijing 100190, China;3.University of Chinese Academy of Sciences, Beijing 100190, China;4.Guang Dong Electric Power Design Institute, China Energy Engineering Group, Guangzhou 510663, China
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| Abstract: |
| The emergence of open mobile platform accelerates the development of service composition in mobile application. However, most current mobile applications fulfill service through static and clustering-based composition. It is prone to "software function overloading" and overlong service accessing path, hindering the efficient use for the users. In this paper, an exploratory service composition method for mobile application. With this method, candidate composable services are provided to the user when the context changes and the selected service(s) is(are) composed into the application just in time. To acquire the candidate services, association rules between the contexts and services are mined based on the history of service selection by different users in different contexts, and used as the matching basis. Further, the traditional FP-tree algorithm is extended to enable the mining of two-dimensional items in mobile application. Experiments show that the extended algorithm has higher precision and recall rate than the traditional method in matching for candidate services. |
| Key words: exploratory service composition context-aware mobile application association rules FP-tree |
