Towards Practical Semantic Web Service Discovery

Abstract

Abstract. Service orientation is a promising paradigm for offering and consuming functionalities within and across organizations. Ever increasing acceptance of service oriented architectures in combination with the acceptance of the Web as a platform for carrying out electronic business triggers a need for automated methods to find appropriate Web services.Various formalisms for discovery of semantically described services with varying expressivity and complexity have been proposed in the past. However, they are difficult to use since they apply the same formalisms to service descriptions and requests. Furthermore, an intersection-based matchmaking is insufficient to ensure applicability of Web services for a given request. In this paper we show that, although most of prior approaches provide a formal semantics, their pragmatics to describe requests is improper since it differs from the user intention. We introduce distinct formalisms to describe functionalities and service requests. We also provide the formal underpinning and implementation of a matching algorithm.

Using Semantic Web Technologies to Query and Manage Information within Federated Cyber-Infrastructures

“…Semantic Web service discovery [14,15] addresses the automated discovery of Web services that satisfy given requirements. The discovery process uses a matchmaking algorithm to find potential Web services that might solve the problem at hand.…”

Semantic Web Service Search: A Brief Survey

“…I/O P/E logic non-logic adaptive iSeM (2012) [30] OWL-S OWLS-MX3 (2012) [29] OWL-S SPARQLent (2010) [55] OWL-S SeMa 2 (2012) [46] OWL-S OWLS-SLR (2010) [47] OWL-S XSSD (2013) [42] OWL-S OWLS-iMatcher (2008) [23] OWL-S OPOSSUM (2007) [59] OWL-S Nuwa (2012) [25] OWL-S, SAWSDL SAWSDL-iMatcher (2011) [65] SAWSDL LOG4SWS (2012) [40] SAWSDL COV4SWS (2012) [ [20] WSML XAM4SWS (2010) [41] hRESTS, microWSMO PSemMa (2012) [5] prop. MDSM (2008) [34] PIM4SWS (meta-model) ( ) iServe (2010) [51] MSM (meta-model) classifier with an evidential coherence-based weighting scheme.…”

Leveraging Fragmental Semantic Data to Enhance Services Discovery

“…OWLS-MX [10] and WSMO-MX [11] propose to combine logic-based reasoning and syntactic concept similarity computations in OWL-S. Sbodio et al [12] propose to use SPARQL as a formal language to describe the pre-and post-conditions of services. Junghans et al [13] propose a practical formalism to describe functionalities and service requests. In contrast, we focus on enriching domain ontology and leveraging it to classify services.…”