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, a collaborative tagging-based environment for Web service discovery, allowing users to tag or annotate a Web service using keyword or free-text. Our system proposes consequently two types of query to search tagged Web services: keyword based and free-text. We put in place an advanced mode in the discovery by keyword
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
Under grid environment, a resource discovery mechanism could dramatically affect both performance and efficiency of the system. Currently, however, since most models of grid discovery are centralized, keyword based matching ones, outcomes of discovery could seldom cater customers' needs. This paper puts forward a grid
Traditional web service search technology based on keyword is time consuming and inefficient. The search results are rather inaccurate. The essential reason is that description of Web Service lacks semantic information. Search Engines can't achieve the interaction automatically and intelligently among services. In
importance. Most existing web service discovery and recommendation approaches focus on either perishing UDDI registries, or keyword-dominant web service search engines, which possess many limitations such as poor recommendation performance and heavy dependence on correct and complex queries from users. It would be desirable for
Existing Web API search engines allow for only category-based browsing and keyword or tag-based searches for RESTful services without offering the capability of discovering and composing real-world RESTful services from the viewpoint of application developers. Therefore, we propose a novel approach, referred to as TAD
as the first factor, then QoS properties being considered as secondary factors. Our approach considers QoS profit values to compute the QoS similarity. In this paper, we apply a spatial clustering technique called the Spherical Associated Keyword Space which is projected clustering result from a three-dimensional sphere
With increasing adoption and presence of Web services, designing novel approaches for efficient Web services recommendation has become steadily more important. Existing Web services discovery and recommendation approaches focus on either perishing UDDI registries, or keyword-dominant Web service search engines, which
(UDDI) was not designed to accommodate these emerging requirements. To solve the problems of storing QoS in UDDI and aggregating QoS values, three different approaches, namely type, keyword based and ontological approaches to model QoS tModel (technical model) have been proposed. The aim is to study these approaches and
Discovering Web services using keyword-based search techniques offered by existing UDDI APIs (i.e. Inquiry API) may not yield results that are tailored to clients' needs. When discovering Web services, clients look for those that meet their requirements, primarily the overall functionality and quality of service (QoS
Web service selection involves finding services from a possibly large database of similar services. The challenges involved in finding a suitable service include large time consumption, and difficulty of finding a perfect match according to the user specified search keywords. For instance, users may have privacy and
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
To discovery Web services in Internet, many approaches have been proposed such as UDDI and DWS. The problem of those methods is that they are just a kind of simple syntax match based on keywords. They make the match inflexible, sometimes even unfaithful. This paper proposes a new algorithm to discover web services
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