Découverte de services basée sur leurs protocoles de conversation
Bibliographic record
Abstract
La découverte de services utiles à une application devient de plus en plus critique dans plusieurs domaines.Les approches de découverte actuelles, basées sur l'appariement des entrées/sorties, ou même complétées par des ontologies, sont limitées car elles ne prennent pas en compte l'aspect sémantique de ces services.Aussi, la sélectivité de ces approches reste très faible ; il revient à l'utilisateur de naviguer sur les nombreux résultats pour retrouver les services qui l'intéressent.Dans cet article, nous affirmons qu'une approche basée sur le comportement des services(en particulier leurs protocoles de conversation) peut aider à sélectionner les meilleurs services et à réduire l'effort de navigation de l'utilisateur.Ceci est d'autant plus important que la découverte peut se faire de façon programmée et dynamique.L'approche proposée se base sur un appariement sémantique des graphes de processus, délivrant aussi bien des résultats exacts que des résultats approchés.Des opérations d'édition permettent de modifier le graphe requête pour le rapprocher le plus possible des graphes cibles selon une distance associée à chaque requête.Nous illustrons notre approche par un exemple basé sur des protocoles de conversation exprimés en utilisant le langage WSCL.ABSTRACT.The capability to easily find useful services becomes increasingly critical in several fields.Current approaches for services retrieval are mostly limited to the matching of their inputs/outputs, possibly annotated with ontologies.Recent works have demonstrated that this approach is not sufficient to discover relevant components.In this paper we argue that, in many situations, the service discovery should be based on the specification of service behavior (in particular, the conversation protocol).The idea behind is to develop matching techniques that operate on behavior models and allow delivery of partial matches as well as their semantic distance with user requirements.A set of edit operations alter query graph to make it as close as possible to target graphs, depending on a distance fixed for each query graph.We exemplify our approach for conversation protocol matchmaking by using the WSCL language.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 0.005 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".