Improved Matchmaking Algorithm for Semantic Web Services Based on Bipartite Graph Matching

Bellur, Umesh; Kulkarni, Rekha P.

doi:10.1109/icws.2007.105

Cited by 105 publications

(92 citation statements)

References 6 publications

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“…To solve the problems mentioned in previous section, we introduce in this section another approach [5] towards semantic matchmaking which makes use of bipartite graph matching to produce a match. The algorithm also introduces a different set of rules of match between concepts in which PlugIn and Subsume levels are interchanged in their degree of match.…”

Section: Bipartite Graph Based Matchingmentioning

confidence: 99%

“…It can be proved that with the above weighting scheme, a matching in which Σwi is minimized is equivalent to matching in which max(wi) is minimised [5]. Matchmaking Algorithm The search procedure accepts a query as input and tries to match its output concepts and input concepts with each advertisement.…”

Section: Bipartite Graph Based Matchingmentioning

confidence: 99%

“…Original algorithm proposed by [5] was based on matching of input and output terms only. However, precondition and effect matching can also be added using same bipartite graph based technique as discussed in [6].…”

Section: Addition Of Precondition and Effect Matchingmentioning

confidence: 99%

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Semantic Matchmaking Algorithms

Bellur¹,

Vadodaria²,

Gupta‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬³

2008

Greedy Algorithms

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Section: Bipartite Graph Based Matchingmentioning

confidence: 99%

Section: Bipartite Graph Based Matchingmentioning

confidence: 99%

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Semantic Matchmaking Algorithms

Bellur¹,

Vadodaria²,

Gupta‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬³

2008

Greedy Algorithms

Self Cite

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“…However, the matching of the clustering concepts in Woogle belongs to syntactic methods since there is no logic reasoning used. The method proposed in [5] exploits bipartite graph to match the input and output annotations of services respectively without considering the syntactic descriptions. The work in [18] considers only the matching of WSDL structures and ignores the matching of semantic annotations.…”

Section: Related Workmentioning

confidence: 99%

SAWSDL Service Discovery Based on Fine-Grained Data Semantics

Wei

Wang

2011

IEICE Trans. Inf. & Syst.

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SUMMARYWith the aim to improve the effectiveness of SAWSDL service discovery, this paper proposes a novel discovery method for SAWSDL services, which is based on the matchmaking of so-called finegrained data semantics that is defined via sets of atomic elements with built-in data types. The fine-grained data semantics can be obtained by a transformation algorithm that decomposes parameters at message level into a set of atomic elements, considering the characteristics of SAWSDL service structure and semantic annotations. Then, a matchmaking algorithm is proposed for the matching of fine-grained data semantics, which avoids the complex and expensive structural matching at the message level. The fine-grained data semantics is transparent to the specific data structure of message-level parameters, therefore, it can help to match successfully similar Web services with different data structures of parameters. Moreover, a comprehensive measure is proposed by considering together several important components of SAWSDL service descriptions at the same time. Finally, this method is evaluated on SAWSDL service discovery test collection SAWSDL-TC2 and compared with other SAWSDL matchmakers. The experimental results show that our method can improve the effectiveness of SAWSDL service discovery with low average query response time. The results imply that fine-grained parameters fit to represent the data semantics of SAWSDL services, especially when data structures of parameters are not important for semantics.

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“…The implemented matching algorithm uses bipartite graph matching [3] to determine the degree of interoperability between the service request and the offered services in the local repository. Some modifications had to be made to the original algorithm to include the current context into the matchmaking process.…”

Section: Service Matchmaking Algorithmmentioning

confidence: 99%

Ontology-Driven Dynamic Discovery and Distributed Coordination of a Robot Swarm

Bouten

Hristoskova

Ongenae

et al. 2012

Dependable Networks and Services

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Abstract. Swarm robotic systems rely heavily on dynamic interactions to provide interoperability between the different autonomous robots. In current systems, interactions between robots are programmed into the applications controlling them. Incorporating service discovery into these applications allows the robots to dynamically discover other devices. However, since most of these mechanisms use syntax-based matching, the robots cannot reason about the offered functionality. Moreover, as contextual information is often not included in the matching process, it is impossible for robots to select the most suitable device under the current context. This paper aims to tackle these issues by proposing a framework for semantic service discovery in a dynamically changing environment. A semantic layer was added to an existing discovery protocol, offering a semantic interface. Using this framework, services can be searched based on what they offer, with services best suiting the current context yielding the highest matching scores.

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Improved Matchmaking Algorithm for Semantic Web Services Based on Bipartite Graph Matching

Abstract: Abstract

Cited by 105 publications

References 6 publications

Semantic Matchmaking Algorithms

Semantic Matchmaking Algorithms

SAWSDL Service Discovery Based on Fine-Grained Data Semantics

Ontology-Driven Dynamic Discovery and Distributed Coordination of a Robot Swarm

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