Similarity based web service matchmaking

Similarity based web service matchmaking

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Similarity Based Semantic Web Service Match

This service is more advanced with JavaScript available, learn more at http: WISM Web Information Systems and Mining pp Cite as. Semantic web service discovery aims at returning the most matching advertised services to the service requester by comparing the semantic of the request service with an advertised service. In this paper we proposed an algorithm to calculate the semantic similarity of two services by weighted averaging their inputs and outputs similarities.

Case study and applications show the effectiveness of our algorithm in service match. Unable to display preview. Download preview PDF. Skip to main content. Advertisement Hide. Conference paper. This is a preview of subscription content, log in to check access. Srinivasan, N. Paolucci, M. Semantic Matching of Web Services Capabilities. Horrocks, I. ISWC LNCS, vol.

Ganesan, P. Exploiting hierarchical domain structure to compute similarity. Gunay, A. Psaila, G. EC-Web Ziegler, P. Ioannidis, Y. EDBT Bernstein, A. K-CAP Workshop on: Ontology Management: Qiu, L. Semantic Markup for Web Services , http: Shi, Z. A Logic Foundation for the Semantic Web. Chang, L. Dynamic Description Logic: Embracing Actions into Description Logic.

Sirin, E. Web Semantics: Peng, H. Personalised recommendations. Cite paper How to cite? ENW EndNote. Buy options.

This category-based keyword-browsing method is clearly insufficient. In Web service matchmaking process, these similarity assessment methods can be used . Semantic web service discovery aims at returning the most matching advertised P.: Structure and Semantic Similarity Metrics for Web Service Matchmaking.

This service is more advanced with JavaScript available, learn more at http: WISM Web Information Systems and Mining pp Cite as.

UltiMatch-NL applies two filters namely Signature-based and Description-based on different abstraction levels of a service profile to achieve more accurate results. More specifically, the proposed filters rely on semantic knowledge to extract the similarity between a given pair of service descriptions.

Skip to search form Skip to main content. With the increasing growth in popularity of Web services, matchmaking of relevant Web services becomes a significant challenge. UDDI provides limited search facilities allowing only a keyword-based search of businesses, services, and the so called tModels based on names and identifiers.

Similarity-based Web service matchmaking

Conceived and designed the experiments: Performed the experiments: Analyzed the data: Wrote the paper: KM MK. Supervised the research and coordinated the project:

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