Semantic Web Based Execution-time Merging Of Processes
Notice bibliographique
Résumé
A process is a series of actions executed in a particular environment in order to achieve a goal. It is often the case that several concurrent processes coexist in an environment in order to achieve several goals simultaneously. However, executing multiple processes is not always a possibility in an environment due to the following reasons: (1) All processes might be needed to be executed by a single agent that is not capable of executing more than one process at a time; (2) Multiple processes may have interactions between them that hamper their concurrent executions by multiple agents. As an example, there might be conflicting actions between several processes that their concurrent execution will stop those processes from achieving their goals. The existing solution to address the abovementioned complications is to merge several processes into a unified conflict-free and improved process before execution. This unified merged process is then executed by a single agent in order to achieve goals of all processes. However, we believe this is not the optimal solution because (a) in some environments, it is unrealistic to assume execution of all processes merged into one single process can be delegated to a single agent; (b) since merging is performed before actual execution of the unified process, some of the assumptions made regarding execution flow in individual processes may not be true during actual execution which will render the merged process irrelevant. In this paper, we propose a semantic web based solution to merge multiple processes during their concurrent execution in several agents in order to address the above-mentioned limitations. Our semantic web Process Merging Framework features a Web Ontology Language (OWL) based ontology called Process Merging Ontology (PMO) capable of representing a wide range of workflow and institutional Process Merging Constraints, mutual exclusivity relations between those constraints and their conditions. Process Merging Constraints should be respected during concurrent execution of processes in several agents in order to achieve execution-time process merging. We use OWL axioms and Semantic Web Rule Language (SWRL) rules in the PMO to define the formal semantics of the merging constraints. A Process Merging Engine has also been developed to coordinate several agents, each executing a process pertaining to a goal, to perform process merging during execution. This engine runs the Process Merging Algorithm that utilizes Process Merging Execution Semantics and an OWL reasoner to infer the necessary modifications in actions of each of the processes so that Process Merging Constraints are respected. In order to evaluate our framework we have merged several clinical workflows each pertaining to a disease represented as processes so that they can be used for decision support for comorbid patients. Technical evaluations show efficiency of our framework and evaluations with the help of domain expert shows expressivity of PMO in representation of merging constraints and capability of Process Merging Engine in successful interpretation of the merging constraints. We plan to extend our work to solve problems in business process model merging and AI plan merging research areas.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,003 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,004 | 0,009 |
| Science ouverte | 0,003 | 0,005 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».