@inproceedings{pub5117,
    abstract = {In this paper, we present SAWSDL-MX2, a hybrid semantic Web service matchmaker for SAWSDL services. Building on our initial work, we adopt logic-based as well as text similarity service selection for model references and add a structural approach, which operates on the pure syntactic description of WSDL elements. The integration of these matching variants is accomplished using a Support Vector Machine (SVM) with non-linear kernel, thus automatically adapting an aggregation function based on previously experienced training data. Results of our performance evaluation based on the standard measures recall and precision over the SAWSDL-TC1 test collection as well as an exhaustive example for all basic matching variants are also given.},
    year = {2009},
    title = {SAWSDL-MX2: A Machine-Learning Approach for Integrating Semantic Web Service Matchmaking Variants},
    booktitle = {2009 IEEE International Conference on Web Services. IEEE International Conference on Web Services (ICWS-2009), 7th, July 6-10, Los Angeles,, CA, United States},
    editor = {Ernesto Damiani and Rong Chang and Jia Zhang},
    pages = {335-342},
    isbn = {978-0-7695-3709-2},
    publisher = {IEEE Press},
    author = {Matthias Klusch and Patrick Kapahnke and Ingo Zinnikus}
}