A Graph Approach for Enhancing Process Models Matchmaking

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dc.contributor.authorBelhoul, Yacine
dc.contributor.authorYahiaoui, Saïd
dc.contributor.authorHaddad, Mohammed
dc.contributor.authorGater, Ahmed
dc.contributor.authorKheddouci, Hamamache
dc.contributor.authorBouzeghoub, Mokrane
dc.date.accessioned2023-05-10T09:56:18Z
dc.date.available2023-05-10T09:56:18Z
dc.date.issued2015-06-27
dc.description.abstractRecent attempts have been done to measure similarity of process models based on graph matching. This problem is known to be difficult and its computational complexity is exponential. Thus, heuristics should be proposed to obtain approximations. Spectral graph matching methods, in particular eigenvalue-based projections, are know to be fast but they lost some quality in the obtained matchmaking. In this paper, we propose a graph approach for the problem of inexact matching of process models. Our approach combines a spectral graph matching method and a string comparator based algorithm in order to improve the quality of process models matchmaking. The proposed method performs the matchmaking at both structural and semantic levels. Experimentation is provided to show the performance of our method to rank a collection of process models according to a particular user query, compared to previous work.
dc.identifier.citation2015 IEEE International Conference on Services Computing (SCC)
dc.identifier.isbn978-1-4673-7281-7
dc.identifier.urihttps://dl.cerist.dz/handle/CERIST/971
dc.language.isoen
dc.publisherIEEE
dc.subjectProcess models matchmaking
dc.subjectProcess models retrieval
dc.subjectSpectral graph
dc.subjectStructural and semantic matching
dc.titleA Graph Approach for Enhancing Process Models Matchmaking
dc.typeConference paper
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