Review of "WordNet: an electronic lexical database" by Christiane Fellbaum. The MIT Press 1998.
Computational Linguistics
A semantic approach to approximate service retrieval
ACM Transactions on Internet Technology (TOIT)
Process-context aware matchmaking for web service composition
Journal of Network and Computer Applications
Building Quick Service Query List Using Wordnet for Automated Service Composition
APSCC '08 Proceedings of the 2008 IEEE Asia-Pacific Services Computing Conference
OWLS-MX: A hybrid Semantic Web service matchmaker for OWL-S services
Web Semantics: Science, Services and Agents on the World Wide Web
Semantic annotations for web services discovery and composition
Computer Standards & Interfaces
Context-Based Matching and Ranking of Web Services for Composition
IEEE Transactions on Services Computing
Structural and Role-Oriented Web Service Discovery with Taxonomies in OWL-S
IEEE Transactions on Knowledge and Data Engineering
Template-Based Adaptation of Semantic Web Services with Model-Driven Engineering
IEEE Transactions on Services Computing
Semantic Web service discovery using natural language processing techniques
Expert Systems with Applications: An International Journal
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The main aspect of Service Oriented Architecture (SOA) is the ability to automatically discover and invoke web services. In web services the syntactic nature of the WSDL forced UDDI to feature only keyword-based matches that often leads to the discovery of more irrelevant services, which ultimately reduce the precision and recall of the search. Semantic web services had been proposed to overcome the issues such as interface heterogeneity and keyword-based syntactic search. The service discovery methods in semantic web services generally require a user query which is used to match the Inputs, Outputs, Precondition and Effect (IOPE) present in the service profile of the OWL-S. This type of matching restricts the users to use the queries that must be of the same context as that of the IOPEs present in the OWL-S. In this work a content-based semantic discovery architecture is proposed, in which the users can use their desired text document as input. The text document after passing through several refinement processes, the nouns are separated. This approach uses the WordNet lexical database, to find the meaning of the extracted nouns which are used for the discovery.