Abstract
Web service discovery is the process of finding a suitable Web service for a given user’s query through analyzing the web service‘s WSDL content and finding the best match for the user’s query. The service query should be written in the same language of the WSDL, for example English. Cross Language Information Retrieval techniques does not exist in the web service discovery process. The absence of CLIR methods limits the search language to the English language keywords only, which raises the following question “How do people that do not know the English Language find a web service, This paper proposes the application of CLIR techniques and IR methods to support Bilingual Web service discovery process the second language that proposed here is Arabic. Text mining techniques were applied on WSDL content and user’s query to be ready for CLIR methods. The proposed model was tested on a curated catalogue of Life Science Web Services http://www.biocatalogue.org/ and used for solving the research problem with 99.87 % accuracy and 95.06 precision
Highlights
Web service discovery aims at finding services whose description matches that of a desired service
The goal of a CrossLanguage Information Retrieval (CLIR) system is to help searchers find documents that are written in languages that are different from the language in which their query is expressed
Bilingual term lists are extensively used as a resource for dictionary-based Cross-Language Information Retrieval (CLIR), in which the goal is to find documents written in one natural language based on queries that are expressed in another
Summary
Web service discovery aims at finding services whose description matches that of a desired service. All of the above work index service metadata found either in a WSDL file (i.e., the tag) or from a Universal, Description, Discovery, and Integration (UDDI) registry entry. In both cases, service metadata written in English are manually created by service providers. The specific objective of our research is to apply CLIR in the web services discovery; this is done by modifying the Match Maker process by adding CLIR components to support the Cross language web service discovery Applying this approach leads to enable different stakeholders to search for web services using their natural language, especially in the new operating systems like Android , Windows 8 metro applications and Apple IOS.
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