Algorithm for Web Services Matching

Sajjanhar, Atul; Hou, Jingyu; Zhang, Yanchun

doi:10.1007/978-3-540-24655-8_72

Cited by 54 publications

(45 citation statements)

References 2 publications

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“…The standardization of the web service description makes the discovery process easier [5]. Several approaches have been proposed to improve the accuracy of Web service discovery by applying several techniques like data mining [7] [6], singular vector decomposition [8], graph based methods, ontology based discovery frameworks, agent based and logic based methods.…”

Section: Issues With Traditional Semantic Web Service Discovery Servicesmentioning

confidence: 99%

A Survey on Semantic Web Service Discovery Methods

Priyadharshini.¹,

R.Gunasri²,

B³

2013

IJCA

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Semantic web services focuses on providing automation and dynamics to existing web service technologies. A large amount of effort and money has been invested in the field of semantic web service discovery. In traditional web service discovery techniques, users need to select relevant web services manually from an extensive textual list. This paper provides an in-depth analysis on the existing approaches available for the discovery of semantic web services.

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Section: Issues With Traditional Semantic Web Service Discovery Servicesmentioning

confidence: 99%

A Survey on Semantic Web Service Discovery Methods

Priyadharshini.¹,

R.Gunasri²,

B³

2013

IJCA

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“…Several Information Retrieval (IR) techniques have been proposed as a way to improve the efficacy of service matching in UDDI. Sajjanhar et al [4] have studied Latent Semantic Indexing (LSI), the prevailing method for small document collections, to capture the semantic associations between short textual advertisements of registered web services. Recently Corella et al [5] have developed a heuristic approach for the semi-automatic classification of web services, assuming that a corpus of previously classified services is available.…”

Section: Related Workmentioning

confidence: 99%

Leveraging Web Services Discovery with Customizable Hybrid Matching

Kokash

Heuvel

D’Andrea

2006

Service-Oriented Computing – ICSOC 2007

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Abstract. Improving web service discovery constitutes a vital step for making the Service Oriented Computing (SOC) vision of dynamic service selection, composition and deployment, a reality. Matching allows for comparing service requests of users with descriptions of available service implementations, and sits at the heart of the service discovery process. During the last years, several matching algorithms for comparing user requests to service interfaces have been suggested, but unfortunately there are no consistent comparative experimental evaluations of existing service discovery methods. This paper firstly reviews several state-ofthe-art approaches to matching using syntactic, semantic and structural information from service interface descriptions. Secondly, it evaluates the efficacy of several key similarity metrics that underpin these approaches, using a uniform corpus of web services. Thirdly, this paper develops and experiments with a novel style of matching that allows for blending various existing matching approaches and makes them configurable to cater service discovery given domain-specific constraints and requirements.

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“…Wang and Stroulia in [2] employed the inverted file to index and search natural language description of desired services. Platzer and Dustdar in [3] also used the Vector Space Model (VSM) to implement a search engine for a Web service, and Sajjanhar et al have attempted to leverage Latent Semantic Analysis (LSA), a variant of VSM, for Web services discovery [4].…”

Section: Introductionmentioning

confidence: 99%

Cross-Language Semantic Web Service Discovery to Improve the Selection Mechanism by using Data Mining Techniques

Eldin¹,

Khedr²,

Al-sharif³

2015

IJCA

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Web service became one of the important methods for communication through the internet and its usage increased in the levels of users and developers. Semantic web service represents the second generation of web services that contains more description and information about its contents. Searching and dealing with web service is done through process called web service discovery which returns a Semantic Web Service Description Language file (SWSDL) for each web service. This research aims to expand the semantic web service usage through adding the multilanguage capability to the web service's discovery process and through recommending other web services to the user based on his history in using web services. These aims were achieved by modifying the web service discovery model through adding two important techniques the Cross Language Information Retrieval (CLIR) technique and the data mining association rules technique. This research proposed two sub models, the first sub model proposed the application of CLIR techniques and information retrieval method to support Bilingual Web service discovery process the second language that proposed here is Arabic.Text mining techniques were applied on SWSDL content and user's query to be ready for CLIR methods, this sub model was tested on a curated catalogue of Life Science Web Services http://www.biocatalogue.org/ and achieving 99.38 % accuracy and 87.23 precision of the effectiveness of the monolingual system. The second sub model proposed a process of web service recommendation by applying the data mining techniques to suggest another web service beside the one he got from the discovery process based on the user's history. This sub model was tested on the mention curated web services site and the results were 65 % of users chose services from the services that recommended by the proposed sub model.

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Algorithm for Web Services Matching

Cited by 54 publications

References 2 publications

A Survey on Semantic Web Service Discovery Methods

A Survey on Semantic Web Service Discovery Methods

Leveraging Web Services Discovery with Customizable Hybrid Matching

Cross-Language Semantic Web Service Discovery to Improve the Selection Mechanism by using Data Mining Techniques

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