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Communication Dans Un Congrès Année : 2019

Discovering crossing-workflow fragments based on activity knowledge graph

Résumé

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.
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Dates et versions

hal-02482868 , version 1 (18-02-2020)

Identifiants

Citer

Jinfeng Wen, Zhangbing Zhou, Yasha Wang, Walid Gaaloul, Yucong Duan. Discovering crossing-workflow fragments based on activity knowledge graph. OTM 2019: On the Move to Meaningful Internet Systems Conferences: Confederated International Conferences: CoopIS, ODBASE, C&TC, Oct 2019, Rhodes, Greece. pp.515-532, ⟨10.1007/978-3-030-33246-4_32⟩. ⟨hal-02482868⟩
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