dc.contributor.author | MARGINEAN, Anca | |
dc.contributor.author | LETIA, Ioan Alfred | |
dc.contributor.author | ZAPOROJAN, Sergiu | |
dc.date.accessioned | 2021-10-12T10:49:41Z | |
dc.date.available | 2021-10-12T10:49:41Z | |
dc.date.issued | 2014 | |
dc.identifier.citation | MARGINEAN, Anca, LETIA, Ioan Alfred, ZAPOROJAN, Sergiu. Using Domain Specific Hierarchical Good Practice for Ranking Service Compositions. In: 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing: proc. IEEE SYNASC-2014, 22-25 Sept. 2014, Timisoara, Romania, art. N. 14918163. | en_US |
dc.identifier.uri | https://doi.org/10.1109/SYNASC.2014.35 | |
dc.identifier.uri | http://repository.utm.md/handle/5014/17691 | |
dc.description | Access full text - https://doi.org/10.1109/SYNASC.2014.35. Este ataşată prezentarea. | en_US |
dc.description.abstract | We propose a method for ranking the service compositions according to the good practice of each domain. Knowledge about good practice is modeled in a hierarchical manner inspired from Hierarchical Task Networks. In describing the good practice knowledge we give a model for HTN in N3 notation and we enhanced it with an importance value. Each candidate service composition is checked against good practice in a model checking style. A candidate composition is a sequence of services. The candidate composition is compared to the constraints defined in good practice and is considered good if for each simple task the most important constraints are fulfilled. | en_US |
dc.language.iso | en | en_US |
dc.publisher | IEEE | en_US |
dc.rights | Attribution-NonCommercial-NoDerivs 3.0 United States | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/us/ | * |
dc.subject | service compositions | en_US |
dc.title | Using Domain Specific Hierarchical Good Practice for Ranking Service Compositions | en_US |
dc.type | Article | en_US |
The following license files are associated with this item: