Multi-Strategy Web Service Discovery for Smart Government

2014 ◽  
Vol 536-537 ◽  
pp. 625-631 ◽  
Author(s):  
Yun Yun Du ◽  
Xue Qin
Keyword(s):  
Web Service ◽  
Service Discovery ◽  
Large Scale ◽  
Search Space ◽  
Semantic Matching ◽  
Business Systems ◽  
Keyword Query ◽  
Web Service Discovery ◽  
Wide Range ◽  
Smart Government

Semantic Web Service technology is the solution to system integration and business collaboration for smart government which is cross-border and heterogeneous on a large scale. However the tremendous Web services search space caused by the wide range, large scale and complex e-government business systems is one of the great challenges for smart government. The paper focuses on researches about service discovery in e-government business integration for smart government. In accordance with the application environment and the current technical status of e-government, the author proposes a multi-strategy Web service discovery method on the basis of the proposed semantic model. The discovery process comprises three stages: keyword query with semantic enhancement, IO semantic matching and PE semantic matching. Finally similarity calculating method is proposed to evaluate the matching degree of each candidate service for service selection as well as the conclusions.

Semantic Web Service Discovery

2011 ◽  
pp. 240-280 ◽  
Author(s):  
V. Tsetsos
Keyword(s):  
Semantic Web ◽  
Web Service ◽  
Service Discovery ◽  
Semantic Web Service ◽  
Web Service Discovery ◽  
Wide Range ◽  
Near Future ◽  
Semantic Web Service Discovery ◽  
Current Systems ◽  
Semantic Discovery

This chapter surveys existing approaches to Semantic Web service discovery. Such semantic discovery will probably substitute existing keyword-based solutions in the near future, in order to overcome the limitations of the latter. First, the architectural components along with potential deployment scenarios are discussed. Subsequently, a wide range of algorithms and tools that have been proposed for the realization of Semantic Web service discovery are presented. Moreover, key challenges and open issues, not addressed by current systems, are identified. The purpose of this chapter is to update the reader on the current progress in this area of the distributed systems domain and to provide the required background knowledge and stimuli for further research and experimentation in semantics-based service discovery.

Context-Aware Web Service Clustering and Visualization

2020 ◽  
Vol 17 (4) ◽  
pp. 32-54
Author(s):  
Banage T. G. S. Kumara ◽  
Incheon Paik ◽  
Yuichi Yaguchi
Keyword(s):  
Web Services ◽  
Web Service ◽  
Service Discovery ◽  
Search Space ◽  
Context Aware ◽  
Specific Context ◽  
Web Service Discovery ◽  
Domain Specific ◽  
Clustering Approach ◽  
Service Clustering

With the large number of web services now available via the internet, web service discovery has become a challenging and time-consuming task. Organizing web services into similar clusters is a very efficient approach to reducing the search space. A principal issue for clustering is computing the semantic similarity between services. Current approaches do not consider the domain-specific context in measuring similarity and this has affected their clustering performance. This paper proposes a context-aware similarity (CAS) method that learns domain context by machine learning to produce models of context for terms retrieved from the web. To analyze visually the effect of domain context on the clustering results, the clustering approach applies a spherical associated-keyword-space algorithm. The CAS method analyzes the hidden semantics of services within a particular domain, and the awareness of service context helps to find cluster tensors that characterize the cluster elements. Experimental results show that the clustering approach works efficiently.

A Multilevel Index Model to Expedite Web Service Discovery and Composition in Large-Scale Service Repositories

2016 ◽  
Vol 9 (3) ◽  
pp. 330-342 ◽  
Author(s):  
Yan Wu ◽  
Chungang Yan ◽  
Zhijun Ding ◽  
Guanjun Liu ◽  
Pengwei Wang ◽  
...  
Keyword(s):  
Web Service ◽  
Service Discovery ◽  
Large Scale ◽  
Web Service Discovery ◽  
Index Model

scholarly journals WEB SERVICE DISCOVERY FOR LARGE SCALE IOT DEPLOYMENTS

2016 ◽  
Vol 4 (1) ◽  
pp. 55-68 ◽  
Author(s):  
Yehia Elshater ◽  
◽  
Khalid Elgazzar ◽  
Patrick Martin ◽  
◽  
...  
Keyword(s):  
Web Service ◽  
Service Discovery ◽  
Large Scale ◽  
Web Service Discovery

Web Service Integration and Management Strategies for Large-Scale Datasets

2011 ◽  
pp. 217-243
Author(s):  
Yannis Panagis ◽  
Evangelos Sakkopoulos ◽  
Spyros Sioutas ◽  
Athanasios Tsakalidis
Keyword(s):  
Web Services ◽  
Web Service ◽  
Service Discovery ◽  
Large Scale ◽  
Management Strategies ◽  
Service Integration ◽  
Service Architecture ◽  
Web Service Discovery ◽  
Large Scale Data ◽  
Scale Data

This chapter presents the Web Service architecture and proposes Web Service integration and management strategies for large-scale datasets. The main part of this chapter presents the elements of Web Service architecture, the challenges in implementing Web Services whenever large-scale data are involved and the design decisions and businessprocess re-engineering steps to integrate Web Services in an enterprise information system. The latter are presented in the context of a case study involving the largest private-sector telephony provider in Greece, where the provider’s billing system datasets are utilized. Moreover, scientific work on Web Service discovery is presented along with experiments on implementing an elaborate discovery strategy over real-world, large-scale data. Thereby, this chapter aims to illustrate the necessary actions to implement Web Services in a corporate environment, stress the associated benefits, to present the necessary business process re-engineering procedures and to highlight the need for more efficient Web Service discovery.

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