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Locating the desired web service to a client requirement is an onerous task as many web services are ready to satisfy a request. Recommending the pertinent web service and not providing the unwarranted service are the two main issues to be addressed in web service selection process. The limitation of keyword search is
Service-Oriented Computing (SOC) is emerging as a new promising computing paradigm. Web service discovery is one of the key issues in SOC. Web service discovery usually provide UDDI as a standard registry which features only keyword-based matches that often give poor performance. Currently approaches for semantic
The aim of service discovery is to discover services based on preferences given by service consumers. Many approaches are using keyword based syntactic methods and recent approaches are using semantic Web technology to enhance service discovery. Traditional service discovery mechanism acts like a black box which
Web service discovery is a vital problem in service computing with the increasing number of services. Existing service discovery approaches merely focus on WSDLbased keyword search, semantic matching based on domain knowledge or ontologies, or QoS-based recommendations. The keyword search omits the underlying
main current approaches for semantic discovery of services are the keyword-based approach and the ontology-based approach. The plain simple keyword matching strategy is time-consuming and has inefficient recall and precision. The ontology-based strategy, on the other hand, is efficient, but may not be practical for the
shut down permanently since 2006. Moreover, keyword-based service discovery is insufficient in coping with complex discovery requirements posed by modern software developers. In this paper, we propose an empirical semantic- based Web service discovery approach. It provides an automatic Web service discovery mechanism that
The important step towards Web service implement is the discovery of required services. Traditional Web service uses UDDI, WSDL standards etc. Keywords based searching is used in the traditional service discovery. For needing manual intervention and lack of semantic description, the methods before have low precision
understand the description of services and add their own descriptions using descriptive tags. Instead of requiring end-users to specify detailed steps for composition, the end-users only need to describe their goals using a few keywords. Our approach expands the meaning of a user’s goal using ontologies then derives a group of
and add their own descriptions using descriptive tags. Instead of specifying the detailed steps for composing a service, a non-expert user would specify the goal of their desired activities using a set of keywords then our approach can automatically identify the relevant services to achieve the goal at run-time. A
The number of available Web services, nowadays, is growing rapidly due their potential in many fields. As a result, the discovery process becomes a challenging issue. Traditional syntactic keywords based discovery techniques are inefficient as they fail to recognize similarities between Web services capabilities. Thus
Aiming to discover the most suitable service cater to the discovery request of service consumer which includes functional requirements and nonfunctional requirements, this paper proposes a service registry model named as SRC (Service Registry on Cloud) which is an extension of the keywords based service registry model
analyzer to pick up information of service and use keywords to find out related services; then we cluster Web services according to the similarity of services; last, we select the appropriate Web service from list of services.
propose a service discovery, which is able to discover all these new service types. In addition, it is capable to find services that are not exact matches of the requested ones. More semantics are introduced through attributes like EquivalenceClass, ParentType and Keywords.
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