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2019 | OriginalPaper | Chapter

N-Gram Representation for Web Service Description Classification

Authors : Christian Sánchez-Sánchez, Leonid B. Sheremetov

Published in: Machine Learning, Optimization, and Data Science

Publisher: Springer International Publishing

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Abstract

Despite increasing availability of Web Services (WS), their automatic processing (classification, grouping or composition) slows down because of the difficulty to read the WSDL service descriptions without related technical knowledge. Categorizing services for automatic service discovery and composition has become a challenging problem. The paper argues that n-gram representation of the data extracted from the different sections of the WSDL description (types, messages and operations) along with the weighing scheme can benefit the classification of services. Experiments are carried out with three different classifiers over available collections of WS descriptions. It is shown that such representations as word bigrams or letter trigrams extracted from WSDL Operations and Types service description features with TF-IDF as n-gram weighting scheme, can improve automatic WS classification.

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Metadata
Title
N-Gram Representation for Web Service Description Classification
Authors
Christian Sánchez-Sánchez
Leonid B. Sheremetov
Copyright Year
2019
Book
Machine Learning, Optimization, and Data Science

Print ISBN: 978-3-030-13708-3

Electronic ISBN: 978-3-030-13709-0

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-030-13709-0_38

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