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In order to increase the effectiveness and speed up the task of finding compatible Web Services in the Brokerage when performing service composition or suggesting Web Services to the requests, high-level functionality of the service needs to be determined. We exploit automatic classification of the Web Service descriptions as well as methodologies to find services and to create an updatable repository of them. We employ a wide range of Machine Learning and Signal Processing algorithms and techniques in order to find the highest precision achievable in the scope of this book for classification…mehr

Produktbeschreibung
In order to increase the effectiveness and speed up the task of finding compatible Web Services in the Brokerage when performing service composition or suggesting Web Services to the requests, high-level functionality of the service needs to be determined. We exploit automatic classification of the Web Service descriptions as well as methodologies to find services and to create an updatable repository of them. We employ a wide range of Machine Learning and Signal Processing algorithms and techniques in order to find the highest precision achievable in the scope of this book for classification of each type of service description. In addition, we complement our approach by showing the importance and effect of contextual information on the classification of the service descriptions and show that it improves the precision. In order to achieve this goal, we gather and store contextual information related to the service descriptions from the sources to the extent of this book. Finally,the result of this effort is a repository of classified service descriptions.
Autorenporträt
Arash Khodadadi, M.C.Sc.: Master of Computer Science at Concordia University. Software Developer at Hypertherm Robotic Software Inc., Montreal, Canada.