Discovery and Scoring of Semantic Web Services based on Client Requirement(s) through a Semantic Search Agent

Çelik, Duygu; Elçi, Atilla

doi:10.1109/compsac.2006.127

Cited by 16 publications

(8 citation statements)

References 1 publication

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“…Apparently, approaches with a higher quadrant ranking are likely to have higher evaluation points, even though there are some exceptions: For instance, the Semantic Agent [49] approach reveals that including only reasoning capabilities is not enough for an autonomic service discovery, but that the consideration of other criteria is important as well. In turn, the Stratus [44], P2P USQL search engine [45], Discovery by Composition [39], and Fuzzy Model [28] approaches come out on top of the approaches based on centralized respectively distributed architectures, as they additionally provide semantic service descriptions and reasoning capabilities.…”

Section: Discussionmentioning

confidence: 99%

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Towards Autonomic Service Discovery A Survey and Comparison

Rambold

Kasinger

Lautenbacher

et al. 2009

2009 IEEE International Conference on Services Computing

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Abstract-Service-oriented architecture has become the standard paradigm for software component integration. However, with the permanently increasing amount of available services and dynamic changes, the complexity of such service infrastructures, their maintenance, and consequently the expenditures spent for their operation increase equally. To deal with these effects, an improvement of service composition and discovery becomes necessary, especially a higher degree of automation. Following the idea of Autonomic Computing, which similarly aims at automating processes and workflows to a high degree, service composition and discovery have to proceed autonomously, which will on the one hand side reduce human involvement to a minimum, but on the other side require certain capabilities on the part of these mechanisms. For these purposes, in this paper we define prime criteria that have to be fulfilled for an autonomic service discovery. Based on that we present a comprehensive survey on existing service discovery approaches and evaluate to which extent they already fulfill these criteria. As a result, the paper reveals that there already exist some approaches that support or even fulfill a couple of the proposed criteria, which principally enables autonomic properties, but what is missing is an holistic approach focusing explicitly on providing autonomic properties.

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Section: Discussionmentioning

confidence: 99%

“…A semantic agent [49] can enrich search keywords through an ontology database. First, the agent sends the keywords to an ontology database and retrieves an ontology which includes the keywords.…”

Section: Surveymentioning

confidence: 99%

Towards Autonomic Service Discovery A Survey and Comparison

Rambold

Kasinger

Lautenbacher

et al. 2009

2009 IEEE International Conference on Services Computing

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“…So, the proposal is a set-based approach using OWL-S. Any reasoning done is for determining subsumption relationships. An implementation of a matcher using the OWL-S/UDDI matchmaker is given by Celik and Elci (2006).…”

Section: Related Work On Matchingmentioning

confidence: 99%

Frame Logic‐based specification and discovery of semantic web services with application to medical appointments

2019

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Matching web services and client requirements in the form of goals is a significant challenge in the discovery of semantic web services. The most common but unsatisfactory approach to matching is set‐based, where both the client and web services declare what objects they require and what objects they can provide. Matching then becomes the simple task of comparing sets of objects. This approach is inadequate because it says nothing about the functionality required by the client or the functionality provided by the web service. As an alternative, we use the Frame Logic as implemented in Flora‐2 to specify web service capabilities and client requirements, including their preconditions, postconditions, and ontologies, implement a logic‐based discovery agent using Flora‐2, demonstrate its usefulness in a medical appointment making scenario, and show its efficiency both theoretically and by benchmarking. The result is an expressive yet concise representation scheme for semantic web services, and a practical, efficient, powerful, and fully implemented matching engine based purely on logical inference for web service discovery, with direct applicability to Web Service Modeling Ontology and Web Service Modeling Language, because both are based on Frame Logic.

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“…Others proposed the utilization of lexical affinities to automatically refine queries [13], and the usage of both the text surrounding the query terms in the search results and the text surrounding the query term in the document being read [16]. Recently, there have been efforts that utilize ontologies for finding query related terms in order to improve retrieval efficiency [14,19]. However, when it comes to large-scale web search engines, the utilization of ontologies in query construction methods is difficult for three reasons [5]: (i) integration is extremely hard, (ii) the web imposes scalability and performance restrictions and (iii) there is a cultural divide between the semantic Web and information retrieval disciplines.…”

Section: Query Refinementmentioning

confidence: 99%

“…The mechanics of their corresponding autosuggest services are not formally disclosed. However, according to various insights, 14 such suggestions most likely derive from some kind of statistical analysis of the queries that have been addressed towards the search engine over time. Thus, it seems that a typical autosuggest service performs well when the searcher picks query suggestions that correspond to:…”

Section: Qualitative Analysis Of the Proposed Autosuggest Functionalitymentioning

confidence: 99%

Semantifying queries over large-scale Web search engines

Papadakis

Stefanidakis

Stamou

et al. 2012

J Internet Serv Appl

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In many situations, searching the web is synonymous to information seeking. Currently, web search engines are the most popular vehicle via which people get access to the web. Their popularity is partially due to the intrinsic way that people interact with them, i.e., by typing some keywords to the corresponding input box. Despite their popularity, search engines often fail to satisfy certain information needs, especially when the latter are haze and poorly articulated. In this paper, we focus on the occasions when largescale web search engines find it difficult to cope with specific information-seeking behaviors and we accordingly introduce a query construction service that is targeted towards the solution of this problem. The proposed service leverages information coming from various DBpedia datasets and provides an intuitive GUI via which searchers determine the semantic orientation of their queries before these are addressed to the underlying search engine. The evaluation of the query construction service justifies the motive of this paper and indicates that it can considerably improve the searchers' querying ability when search engines fail to provide adequate help.

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Discovery and Scoring of Semantic Web Services based on Client Requirement(s) through a Semantic Search Agent

Cited by 16 publications

References 1 publication

Towards Autonomic Service Discovery A Survey and Comparison

Towards Autonomic Service Discovery A Survey and Comparison

Frame Logic‐based specification and discovery of semantic web services with application to medical appointments

Semantifying queries over large-scale Web search engines

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