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International Conference on Machine Learning, Optimization, and Data Science

LOD 2018: Machine Learning, Optimization, and Data Science pp 447–459Cite as

N-Gram Representation for Web Service Description Classification

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11331))

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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Author information

Authors and Affiliations

  1. Universidad Autónoma Metropolitana, Unidad Cuajimalpa, Mexico City, Mexico

    Christian Sánchez-Sánchez

  2. Instituto Mexicano del Petróleo, Mexico City, Mexico

    Leonid B. Sheremetov

Authors
  1. Christian Sánchez-Sánchez
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  2. Leonid B. Sheremetov
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Corresponding author

Correspondence to Christian Sánchez-Sánchez .

Editor information

Editors and Affiliations

  1. University of Catania, Catania, Italy and University of Reading, Reading, UK

    Giuseppe Nicosia

  2. University of Florida, Gainesville, FL, USA

    Panos Pardalos

  3. University of Catania, Catania, Italy

    Giovanni Giuffrida

  4. Harvard University, Cambridge, MA, USA

    Renato Umeton

  5. IBM, Tivoli Research Lab, Rome, Italy

    Vincenzo Sciacca

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Sánchez-Sánchez, C., Sheremetov, L.B. (2019). N-Gram Representation for Web Service Description Classification. In: Nicosia, G., Pardalos, P., Giuffrida, G., Umeton, R., Sciacca, V. (eds) Machine Learning, Optimization, and Data Science. LOD 2018. Lecture Notes in Computer Science(), vol 11331. Springer, Cham. https://doi.org/10.1007/978-3-030-13709-0_38

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

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-13708-3

  • Online ISBN: 978-3-030-13709-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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