An Improved Semantic Annotation Method of Web Services Based on Ontology

Author(s):  
Zhang Lei ◽  
Xiaoying Yang ◽  
Yanni Yuan ◽  
Bo Sun
2014 ◽  
Vol 24 (10) ◽  
pp. 2405-2418 ◽  
Author(s):  
Feng TIAN ◽  
Xu-Kun SHEN

2012 ◽  
Vol 06 (02) ◽  
pp. 243-259
Author(s):  
MOHAMMAD MOURHAF AL ASSWAD ◽  
AUHOOD ALFARIES ◽  
SERGIO DE CESARE ◽  
MARK LYCETT

Semantic web services (SWS) have recently attracted much attention because of their potential to automate all common service tasks such as discovery, composition, invocation and execution. The successful implementation of SWS is profoundly based on the availability of appropriate methods for SWS description. There is, however, no consensus in the SWS arena on the significant service elements that make SWS description comprehensive. Furthermore, semantic annotation of those elements is still a manual process where human involvement is a must. Therefore, automating the annotation process is highly desired as the manual annotation is a difficult, costly and time-consuming process. Few approaches exist aiming to semi-automate the annotation task. These approaches have limitations preventing their wide adoption by the research and practice communities. This paper contributes by analysing and comparing those existing semi-automatic Web service annotation approaches in order to highlight the major challenges and provide fruitful guidelines to aid future research. Particularly, a synthesis of service elements that require semantic annotation is provided and then used to assess the completeness of semi-automated approaches. The comparison leads to significant implications for theory and practice.


2018 ◽  
Vol 14 (2) ◽  
pp. 233-258 ◽  
Author(s):  
Efthimia Mavridou ◽  
Konstantinos M. Giannoutakis ◽  
Dionysios Kehagias ◽  
Dimitrios Tzovaras ◽  
George Hassapis

Purpose Semantic categorization of Web services comprises a fundamental requirement for enabling more efficient and accurate search and discovery of services in the semantic Web era. However, to efficiently deal with the growing presence of Web services, more automated mechanisms are required. This paper aims to introduce an automatic Web service categorization mechanism, by exploiting various techniques that aim to increase the overall prediction accuracy. Design/methodology/approach The paper proposes the use of Error Correcting Output Codes on top of a Logistic Model Trees-based classifier, in conjunction with a data pre-processing technique that reduces the original feature-space dimension without affecting data integrity. The proposed technique is generalized so as to adhere to all Web services with a description file. A semantic matchmaking scheme is also proposed for enabling the semantic annotation of the input and output parameters of each operation. Findings The proposed Web service categorization framework was tested with the OWLS-TC v4.0, as well as a synthetic data set with a systematic evaluation procedure that enables comparison with well-known approaches. After conducting exhaustive evaluation experiments, categorization efficiency in terms of accuracy, precision, recall and F-measure was measured. The presented Web service categorization framework outperformed the other benchmark techniques, which comprise different variations of it and also third-party implementations. Originality/value The proposed three-level categorization approach is a significant contribution to the Web service community, as it allows the automatic semantic categorization of all functional elements of Web services that are equipped with a service description file.


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