An Approach to Web Service Discovery Based on the Semantics

Fan, Jing; Ren, Bo; Xiong, Li

doi:10.1007/11540007_142

Cited by 11 publications

(6 citation statements)

References 2 publications

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“…Their method uses an algorithm using extended semantic annotation, based on web service standards. The critical problems in web service discovery such as how to locate web services and how to select the best one from large numbers of functionally similar web services are explained by Fan, Ren, and Xiong (). Küster and König‐Ries () propose a graded relevance scale for semantic web services matchmaking as measurements to evaluate SWS matchmakers based on such graded relevance scales.…”

Section: Related Work On Matchingmentioning

confidence: 99%

Frame Logic‐based specification and discovery of semantic web services with application to medical appointments

2019

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Matching web services and client requirements in the form of goals is a significant challenge in the discovery of semantic web services. The most common but unsatisfactory approach to matching is set‐based, where both the client and web services declare what objects they require and what objects they can provide. Matching then becomes the simple task of comparing sets of objects. This approach is inadequate because it says nothing about the functionality required by the client or the functionality provided by the web service. As an alternative, we use the Frame Logic as implemented in Flora‐2 to specify web service capabilities and client requirements, including their preconditions, postconditions, and ontologies, implement a logic‐based discovery agent using Flora‐2, demonstrate its usefulness in a medical appointment making scenario, and show its efficiency both theoretically and by benchmarking. The result is an expressive yet concise representation scheme for semantic web services, and a practical, efficient, powerful, and fully implemented matching engine based purely on logical inference for web service discovery, with direct applicability to Web Service Modeling Ontology and Web Service Modeling Language, because both are based on Frame Logic.

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Section: Related Work On Matchingmentioning

confidence: 99%

Frame Logic‐based specification and discovery of semantic web services with application to medical appointments

2019

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“…To calculate the matching degree, they use various methods and focus on different elements of the services descriptions besides taking into account their semantics. They essentially opt for three types of matching: IO-matching (Inputs and Outputs matching) [19][20], PE-matching (Preconditions and Effects matching) [4] and IOPE-matching (Inputs, Outputs, Preconditions and Effects matching) [21][22][23] [24]. In IO-matching, matched elements are limited to inputs and outputs.…”

Section: Deductive Approachmentioning

confidence: 99%

Semantic Web Service Discovery Approaches : Overview and Limitations

Bitar

Belouadha²,

Roudiès³

2014

IJCSES

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“…It concerns data semantics of input (I) and output (O) service parameters. This type of matching is adopted in [7], [8], and [9]. • PE-matching: this category concerns the matching of service/request preconditions (P) and effects (E).…”

Section: A Logic-based Matchingmentioning

confidence: 99%

“…• Compared to [12], [11], [17], [9] and [8] in which the matching is mainly based on inputs and/or outputs, we distinguish Matching Degrees for inputs, outputs, operation, and interface. For example, if one requires a service providing some inputs/outputs within specific interface's goals and/or some operations' capabilities, it is obvious that semantic matching results would be more satisfying and precise than matching all services basically through required inputs/outputs, either syntactically or even semantically like in [11] and [17].…”

mentioning

confidence: 99%

“…For example, if one requires a service providing some inputs/outputs within specific interface's goals and/or some operations' capabilities, it is obvious that semantic matching results would be more satisfying and precise than matching all services basically through required inputs/outputs, either syntactically or even semantically like in [11] and [17]. • We considered that degrees of matching, in some matching mechanisms, either insufficient like in [13], [8] and [9], or unclear like in [12]. In [13], we can find one case of subsumption through the degree SUBSUMES, either selected matching degree would be UNKNOWN or FAIL, that is why we propose two more precise degrees that take into account more specific subsumption matching cases:…”

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confidence: 99%

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YASA-M: A Semantic Web Service Matchmaker

Chabeb

Tata

Ozanne

2010

2010 24th IEEE International Conference on Advanced Information Networking and Applications

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In this paper, we present new algorithms for matching Web services described in YASA4WSDL (YASA for short). We have already defined YASA that overcomes some issues missing in WSDL or SAWSDL. In this paper, we continue on our contribution and show how YASA Web services are matched based on the specificities of YASA descriptions. Our matching algorithm consists of three variants based on three different semantic matching degree aggregations. This algorithm was implemented in YASA-M, a new Web service matchmaker. YASA-M is evaluated and compared to well known approaches for service matching. Experiments show that YASA-M provides better results, in terms of precision, response time, and scalability, than a well known matchmaker.

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An Approach to Web Service Discovery Based on the Semantics

Cited by 11 publications

References 2 publications

Frame Logic‐based specification and discovery of semantic web services with application to medical appointments

Frame Logic‐based specification and discovery of semantic web services with application to medical appointments

Semantic Web Service Discovery Approaches : Overview and Limitations

YASA-M: A Semantic Web Service Matchmaker

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