TY - GEN
T1 - Discovering crossing-workflow fragments based on activity knowledge graph
AU - Wen, Jinfeng
AU - Zhou, Zhangbing
AU - Wang, Yasha
AU - Gaaloul, Walid
AU - Duan, Yucong
N1 - Publisher Copyright:
© Springer Nature Switzerland AG 2019.
PY - 2019/1/1
Y1 - 2019/1/1
N2 - This paper proposes a novel crossing-workflow fragment discovery mechanism, where an activity knowledge graph (AKG) is constructed to capture partial-ordering relations between activities in scientific workflows, and parent-child relations specified upon sub-workflows and their corresponding activities. The biterm topic model is adopted to generate topics and quantify the semantic relevance of activities and sub-workflows. Given a requirement specified in terms of a workflow template, individual candidate activities or sub-workflows are discovered leveraging their semantic relevance and text description in short documents. Candidate fragments are generated through exploring the relations in AKG specified upon candidate activities or sub-workflows, and these fragments are evaluated through balancing their structural and semantic similarities. Evaluation results demonstrate that this technique is accurate and efficient on discovering and recommending appropriate crossing-workflow fragments in comparison with the state of art’s techniques.
AB - This paper proposes a novel crossing-workflow fragment discovery mechanism, where an activity knowledge graph (AKG) is constructed to capture partial-ordering relations between activities in scientific workflows, and parent-child relations specified upon sub-workflows and their corresponding activities. The biterm topic model is adopted to generate topics and quantify the semantic relevance of activities and sub-workflows. Given a requirement specified in terms of a workflow template, individual candidate activities or sub-workflows are discovered leveraging their semantic relevance and text description in short documents. Candidate fragments are generated through exploring the relations in AKG specified upon candidate activities or sub-workflows, and these fragments are evaluated through balancing their structural and semantic similarities. Evaluation results demonstrate that this technique is accurate and efficient on discovering and recommending appropriate crossing-workflow fragments in comparison with the state of art’s techniques.
KW - Activity knowledge graph
KW - Crossing-workflow fragments
KW - Topic discovery
U2 - 10.1007/978-3-030-33246-4_32
DO - 10.1007/978-3-030-33246-4_32
M3 - Conference contribution
AN - SCOPUS:85077842257
SN - 9783030332457
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 515
EP - 532
BT - On the Move to Meaningful Internet Systems
A2 - Panetto, Hervé
A2 - Debruyne, Christophe
A2 - Lewis, Dave
A2 - Hepp, Martin
A2 - Ardagna, Claudio Agostino
A2 - Meersman, Robert
PB - Springer
T2 - Confederated International Conferences on Cooperative Information Systems, CoopIS 2019, Ontologies, Databases, and Applications of Semantics, ODBASE 2019, and Cloud and Trusted Computing, C and TC, held as part of OTM 2019
Y2 - 21 October 2019 through 25 October 2019
ER -