GLUE2: A Web Service Discovery Engine with Non-Functional Properties

Carenini, Alessio; Cerizza, Dario; Comerio, Marco; Valle, Emanuele Della; Paoli, Flavio De; Maurino, Andrea; Palmonari, Matteo; Turati, Andrea

doi:10.1109/ecows.2008.12

Cited by 16 publications

(8 citation statements)

References 7 publications

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“…EMMA -an Enhanced MatchMaking Add-on -was implemented as a configurable OWL-S matchmaking plugin compatible with SME 2 2.1.1. Although EMMA offers a similar precision as × Carenini et al [44] ∼ × Our proposal the prototype evaluated in this article, average query response time is worse than the prototype, because of the way SME 2 plugins register the available services. This issue is identified in the S3 Contest 2010 report, so next version of SME 2 application will allow the use of pre-filtering techniques, such as our proposed solution.…”

Section: Discussionmentioning

confidence: 91%

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Improving semantic web services discovery using SPARQL-based repository filtering

García

Ruiz

Ruiz–Cortés

2012

Journal of Web Semantics

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Section: Discussionmentioning

confidence: 91%

“…Finally, Carenini et al propose a customizable hybrid architecture for SWS discovery and ranking named GLUE2 [44]. GLUE2 offers a set of specialized discovery components, such as functional discovery, dynamic discovery, non-functional discovery, and ranking, among other additional components [52].…”

Section: Related Workmentioning

confidence: 99%

Improving semantic web services discovery using SPARQL-based repository filtering

García

Ruiz

Ruiz–Cortés

2012

Journal of Web Semantics

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“…Thus, other approaches offer more user-friendly facilities to combine these preferences, define NFP-based policies [23,24], and to express qualitative preferences [21].…”

Section: Related Workmentioning

confidence: 99%

“…Proposals that provide components that are easier to integrate, because they offer hybrid architectures [20,24] or SPARQL endpoints [21,10,5] are rated with medium degree of integrability. Finally, [23] is highly integrable because it defines a component-based, hybrid architecture that allows the user to customize the service retrieval and ranking processes.…”

Section: Related Workmentioning

confidence: 99%

Integrating semantic Web services ranking mechanisms using a common preference model

García

Junghans

Ruiz

et al. 2013

Knowledge-Based Systems

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Service ranking has been long-acknowledged to play a fundamental role in helping users to select the best offerings among services retrieved from a search request. There exist many ranking mechanisms, each one providing ad hoc preference models that offer different levels of expressiveness. Consequently, applying a single mechanism to a particular scenario constrains the user to define preferences based on that mechanism's facilities. Furthermore, a more flexible solution that uses several independent mechanisms will face interoperability issues because of the differences between preference models provided by each ranking mechanism. In order to overcome these issues, we propose a Preferencebased Universal Ranking Integration (PURI) framework that enables the combination of several ranking mechanisms using a common, holistic preference model. Using PURI, different ranking mechanisms are seamlessly and transparently integrated, offering a single façade to define preferences using highly expressive facilities that are not only decoupled from the concrete mechanisms that perform the ranking process, but also allow to exploit synergies from the combination of integrated mechanisms. We also thoroughly present a particular application scenario in the SOA4All EU project and evaluate the benefits and applicability of PURI in further domains.

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“…Here a matching algorithm is developed that combines several services which are not known and need to be discovered. In [10], the flexible architecture of the discovery engine Glue2 is proposed which comes with a powerful set of discovery components (for functional matching, non-functional matching, data fetching, etc.) that can be executed in different order as required by specific execution workflows.…”

Section: Introductionmentioning

confidence: 99%