Crossing Scientific Workflow Fragments Discovery Through Activity Abstraction in Smart Campus

doi:10.1109/ACCESS.2018.2857482

CORC > 自动化研究所 > 中国科学院自动化研究所 > 精密感知与控制研究中心 > 人工智能与机器学习

	Crossing Scientific Workflow Fragments Discovery Through Activity Abstraction in Smart Campus
	Wen, Jinfeng 1,2; Zhou, Zhangbing 1,3; Shi, Zhensheng 4; Wang, Junping5,6 ; Duan, Yucong 7; Zhang, Yaqiang 1
刊名	IEEE ACCESS
	2018
卷号	6 页码:40530-40546
关键词	Scientific Workflow Community Discovery Clustering Abstract Activity Cross-workflow Fragment Recommendation
DOI	10.1109/ACCESS.2018.2857482
文献子类	Article
英文摘要	Considering the knowledge-intensity and error-prone of developing scientific workflows from scratch, reusing and repurposing current workflows are the effective and efficient solution to support scientists for conducting novel experiments, and this strategy is deemed as important to achieve the objective of smart campus. An experiment may be relevant with one or multiple scientific workflows. This observation drives us to propose a technique that can discover and recommend cross-workflow fragments with respect to the requirement of novel experiments. Specifically, the functionally similar activities are clustered through adopting a modularity-based community discovery clustering technique, and they are represented as abstract activities. An abstract activity network model is constructed accordingly to reflect the invocation relations among abstract activities. Structural and semantic similar workflow fragments are discovered from the abstract activity network through the sub-graph matching algorithm. These fragments are instantiated through replacing abstract activities by appropriate activities in certain activity clusters. These instantiated workflow fragments are ranked and recommended for their reuse and repurposing purpose. Experimental evaluation results demonstrate that our technique is accurate and efficient on discovering and recommending appropriate cross-workflow fragments.
WOS关键词	SERVICE COMPOSITION ; SENSOR-CLOUD ; BIG DATA ; SIMILARITY ; PATTERNS ; SYSTEMS ; SEARCH ; CITY
WOS研究方向	Computer Science ; Engineering ; Telecommunications
语种	英语
WOS记录号	WOS:000441868800018
资助机构	National Natural Science Foundation of China(61772479 ; Open Foundation of State key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications(SKLNST-2018-1-13) ; Fundamental Research Funds for the Central Universities, China University of Geosciences (Beijing), China ; 61662021)
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/21827]
专题	精密感知与控制研究中心_人工智能与机器学习
作者单位	1.China Univ Geosci Beijing, Sch Informat Engn, Beijing 100083, Peoples R China 2.Beijing Univ Posts & Telecommun, State Key Lab Networking & Switching Technol, Beijing 100876, Peoples R China 3.TELECOM SudParis, Comp Sci Dept, F-91011 Evry, France 4.PetroChina Res Inst Petr Explorat & Dev, Langfang 065007, Peoples R China 5.Chinese Acad Sci, Inst Automat, Lab Precis Sensing, Beijing 100190, Peoples R China 6.Chinese Acad Sci, Inst Automat, Control Ctr, Beijing 100190, Peoples R China 7.Hainan Univ, Coll Informat Sci & Technol, Haikou 570228, Hainan, Peoples R China
推荐引用方式 GB/T 7714	Wen, Jinfeng,Zhou, Zhangbing,Shi, Zhensheng,et al. Crossing Scientific Workflow Fragments Discovery Through Activity Abstraction in Smart Campus[J]. IEEE ACCESS,2018,6:40530-40546.
APA	Wen, Jinfeng,Zhou, Zhangbing,Shi, Zhensheng,Wang, Junping,Duan, Yucong,&Zhang, Yaqiang.(2018).Crossing Scientific Workflow Fragments Discovery Through Activity Abstraction in Smart Campus.IEEE ACCESS,6,40530-40546.
MLA	Wen, Jinfeng,et al."Crossing Scientific Workflow Fragments Discovery Through Activity Abstraction in Smart Campus".IEEE ACCESS 6(2018):40530-40546.