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  • The module for the second group enables service requesters to interact with the search engine to denote their queries by means of service domain knowledge, and then retrieve service information based on the denoted queries. Related items Showing items related by title, author, creator semanhic subject. Hussain and E. Intelligent Agents. Read and print from thousands of top scholarly journals. Personal health system: A tool to support the patient empowerment. RicciG. The evaluation result is then incorporated with the previous results to produce the eventual QoS value of the service advertisement in a service domain. Launch Research Semantic service matchmaking for digital health ecosystems. View 1 excerpt, cites background.

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  • View 2 excerpts, references background. Search for articles published in journals where these words are in the journal name. An intensive survey found that current research cannot support accurate and trustworthy matchmaking between health service requests and health service advertisements in Digital Health Ecosystems. Service-requester-centered service selection and ranking model for digital transportation ecosystems. An intensive survey found that current research cannot support accurate and trustworthy matchmaking between health service semantic service matchmaking for digital health ecosystems and health service advertisements in Digital Matchmakijg Ecosystems. More Filters. Search espace. A framework for formalizing inconsistencies and deviations in human-centered systems. The methodology is presented by the prototype of a Service Search Engine. Informatics This Collection. Please try again! View on PubMed. With sematnic emergence of the Web and its pervasive intrusion on individuals, organizations, businesses etc. Published in Semantic service matchmaking for digital health ecosystems. A service concept recommendation system for enhancing matchnaking dependability of semantic service matchmakers in the service ecosystem environment.

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  • DOI: We are concerned with the large-scale, ambiguous, heterogeneous, and untrustworthy health service information in Digital Semantic service matchmaking for digital health ecosystems Ecosystems. Designing a composite e-service platform with recommendation function. Figures and Tables. Authors Dong, Hai. Metadata Show full item record. The service concept recommendation methodology concerns the issue of incomplete or ecosysteks queries. A framework for discovering and classifying ubiquitous services in digital health ecosystems. A service concept recommendation system for enhancing the dependability of semantic service matchmakers in the service ecosystem environment. Using multi-categorization semantic analysis and personalization for semantic search. Toward a Model of Clinical Trials. Save to Library. Search Reset filters. Supervisor Dr. DOI: However, because of the diversity and heterogeneity of the services in the DEST environment, existing commercial products or research outputs cannot be directly applied to this field so as to fulfill the requirements of SMEs. Consequently, no individual or organization can ignore the huge impact of the Web on social well-being, growth and prosperity, or the changes that digotal has brought about to the world economy, transforming it from a self-contained, isolated, and static environment to an open, connected, dynamic environment. An intensive survey found that current research cannot support accurate and trustworthy matchmaking between semantic service matchmaking for digital health ecosystems service requests and health service advertisements in Digital Health Ecosystems.

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  • Create Alert. This Collection. OAI identifier: oai:espace. View 1 excerpt, cites semantic service matchmaking for digital health ecosystems. Based on the prototype, we test the mathematical algorithms involved in the methodology by a simulation approach and validate the proposed functions of the methodology by a functional testing approach. The methodology for service domain knowledge updating is realized by a voting system for any proposals for changes in service domain knowledge, and by assigning matxhmaking weights to the votes of domain experts and normal users. Multiagent systems: a ecosywtems approach to distributed artificial intelligence. Has PDF. The vision of Digital Ecosystems was initiated by the European Commission, with the purpose of constructing an information and communication technology environment to facilitate the sustainable development of small and medium enterprises. Skip to search form Skip to main content You are currently offline. Service matchmakers play an important role in ensuring the Type Journal Article. Consequently, no individual or organization can ignore the huge impact of the Web on social well-being, growth and prosperity, or the changes that it has brought about to the world economy, transforming it from a self-contained, isolated, and static environment to an open, connected, dynamic environment. Publication Type. View 1 excerpt, references background. Launch Research Feed. The vision of Digital Ecosystems was initiated by the European Commission, with the purpose of constructing an information semantic service matchmaking for digital health ecosystems communication technology environment to facilitate the sustainable development of small and medium enterprises. DOI:

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  • Figures, Tables, and Topics from this paper. Changes resulting from the publishing process, such as peer review, editing, semantic service matchmaking for digital health ecosystems, structural formatting, and other quality control mechanisms matchhmaking not be reflected in this document. SerbanatiF. A Service Semantic service matchmaking for digital health ecosystems is matcgmaking biological view of the business and software environment, which is comprised of a Service Use Ecosystem and a Service Supply Ecosystem. Serbanati and F. Using multi-categorization semantic analysis and personalization for semantic search. Please try again! Multiagent systems: a modern approach to distributed artificial intelligence. The customized semantic service retrieval methodology comprises: 1 a service information discovery, annotation and classification methodology; 2 aervice service retrieval methodology; 3 a service concept recommendation methodology; 4 a quality of service QoS evaluation and service ranking methodology; and 5 a service domain knowledge updating, and service-provider-based Service Description Entity Heallth metadata publishing, maintenance and classification methodology. This article might be available on DeepDyve through a different publisher:. Farookh Khadeer Hussain. Log in. Read and print from thousands of top scholarly journals. JavaScript is disabled for your browser. Authors Dong, Hai. Figures and Topics from this paper. View 2 excerpts, references methods.

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  • Search DeepDyve for Some features of the site may not work correctly. Intelligent Agents. Therefore, in this paper, we propose servoce framework of a semantic service matchmaker, by taking into account the ambiguous, heterogeneous nature of service information in Digital Health Ecosystems. A digital ecosystem is a widespread type of ubiquitous computing environment comprised of ubiquitous, geographically dispersed, and heterogeneous species, technologies and services. Methods Citations. The vision of Digital Ecosystems was initiated by the European Commission, with the purpose of constructing an information and communication technology environment semantic service matchmaking for digital health ecosystems facilitate the sustainable development of small and medium enterprises. Ricci and G. JavaScript is disabled for your browser. Transport service ontology and its application in the field of semantic search.

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  • Design of a terminal solution for integration of in-home health care devices and services towards the Internet-of-Things. The methodology is presented by the prototype of a Service Search Engine. The vision of Digital Ecosystems was initiated by the European Commission, with the purpose of constructing an information and communication technology environment to facilitate the sustainable development of small and medium enterprises. In order rcosystems thoroughly evaluate this framework, we implement a prototype — a Semantic Health Service Search Engine, and execute a series of experiments on the prototype using a functional testing and simulation approach. Search DeepDyve for You can change your cookie settings through your browser. Metadata Show full item record. As a subdomain of the digital ecosystems, Citation Type. Farookh Khadeer Hussain. Publication Type. Search espace. Provided by: espace Curtin. Interacting agents through a web-based health serviceflow management system. View semantic service matchmaking for digital health ecosystems excerpts, references background and methods.

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  • Background Citations. All DeepDyve websites use cookies to improve your online experience. RicciG. View 1 excerpt, cites background. An intensive survey found that current research cannot support accurate and trustworthy matchmaking between health service requests and health service advertisements in Digital Health Ecosystems. Access Status Open access. Metadata Show full item record. View 2 excerpts, references background. View 1 excerpt, references methods. Ecosyetems, Tables, and Topics from this paper.

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