Review of Ontology Based Approaches for Web Service Discovery

Fariss, Mourad; Allali, Naoufal El; Asaidi, Hakima; Bellouki, Mohamed

doi:10.1007/978-3-030-11914-0_8

Cited by 11 publications

(5 citation statements)

References 12 publications

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“…AND DISCOVER WEB SERVICES Several approaches have been developed in recent years in this field, among all those studied; researchers in [11] gives a comparison between ontology and other techniques on the performance parameters to provide challenges of ontology, in Web service discovery, like the potential conversion of existing non-semantic structure to the semantic descriptions and the less research work in the field of semantic web service that targets to enhance qualitatively or upgrade Web service ontologies or can facilitate the use of ontologies and improve the selection process.…”

Section: Different Approaches To Researchmentioning

confidence: 99%

Agent-Based Model for Interpreting a Client Query as Part of Composite Web Service Discovery

Belmabrouk,

Dekhici

2023

IJCDS

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The use of new tools, such as ontologies and agents, is becoming increasingly important in Web services research as they can help us analyze requests and conduct semantic searches for Web services. The main goal of this study is to propose a solution for intelligently interpreting user queries when searching for Web services. The proposed model involves the collaboration of two primary agents: a reactive agent and a cognitive agent. The reactive agent analyzes the user's query and the cognitive agent reasons based on a relevant domain ontology, matching the concepts extracted from the query with the services already published in the UDDI registry. This approach allows for the intentions and desires of the user to be understood, and returns the most suitable service accordingly.

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Section: Different Approaches To Researchmentioning

confidence: 99%

Agent-Based Model for Interpreting a Client Query as Part of Composite Web Service Discovery

Belmabrouk,

Dekhici

2023

IJCDS

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“…This similarity becomes possible with the semantic aspect by utilizing OWL-S services, knowing that there are several methods of semantic description. The choice of an ontology language based on OWL-S is justified in our previous work [4], the most standardized and perhaps the most complete semantic WS deployed technology.…”

Section: Proposed Approachmentioning

confidence: 99%

“…A semantic web services discovery approach integrating multiple similarity measures… (Mourad Fariss) 1229 and selection tasks [4]. Many existing web service discovery approaches are based on operational signing and several matching mechanisms.…”

Section: Introductionmentioning

confidence: 99%

A semantic web services discovery approach integrating multiple similarity measures and k-means clustering

Fariss¹,

Allali²,

Asaidi³

et al. 2021

IJEECS

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Web service (WS) discovery is an essential task for implementing complex applications in a service oriented architecture (SOA), such as selecting, composing, and providing services. This task is limited semantically in the incorporation of the customer’s request and the web services. Furthermore, applying suitable similarity methods for the increasing number of WSs is more relevant for efficient web service discovery. To overcome these limitations, we propose a new approach for web service discovery integrating multiple similarity measures and k-means clustering. The approach enables more accurate services appropriate to the customer's request by calculating different similarity scores between the customer's request and the web services. The global semantic similarity is determined by applying k-means clustering using the obtained similarity scores. The experimental results demonstrated that the proposed semantic web service discovery approach outperforms the state-of-the approaches in terms of precision (98%), recall (95%), and F-measure (96%). The proposed approach is efficiently designed to support and facilitate the selection and composition of web services phases in complex applications.

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“…The work of [26] compare the semantic discovery approaches according to several criteria, such as interface type (e.g. OWL-S, WSMO), the scalability, the request expansion, the adopted similarity measure and the use of natural language processing.…”

Section: B Non-logic-based Matchmakingmentioning

confidence: 99%

Effective Service Discovery based on Pertinence Probabilities Learning

Merzoug¹,

Etchiali²,

Fethallah³

et al. 2021

IJACSA

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Web service discovery is one of the most motivating issues of service-oriented computing field. Several approaches have been proposed to tackle this problem. In general, they leverage similarity measures or logic-based reasoning to perform this task, but they still present some limitations in terms of effectiveness. In this paper, we propose a probabilistic-based approach to merge a set of matching algorithms and boost the global performance. The key idea consists of learning a set of relevance probabilities; thereafter, we use them to produce a combined ranking. The conducted experiments on the real world dataset "OWL-S TC 2" demonstrate the effectiveness of our model in terms of mean averaged precision (MAP); more specifically, our solution, termed "probabilistic fusion", outperforms all the state of the art matchmakers as well as the most prominent similarity measures.

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Review of Ontology Based Approaches for Web Service Discovery

Cited by 11 publications

References 12 publications

Agent-Based Model for Interpreting a Client Query as Part of Composite Web Service Discovery

Agent-Based Model for Interpreting a Client Query as Part of Composite Web Service Discovery

A semantic web services discovery approach integrating multiple similarity measures and k-means clustering

Effective Service Discovery based on Pertinence Probabilities Learning

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