Name
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. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/978-3-030-13709-0_38 | LOD |
Field | DocType | Citations |
Weighting,Computer science,Trigram,Artificial intelligence,n-gram,Natural language processing,Bigram,Automatic processing,Web service,Service discovery,Machine learning | Conference | 0 |
PageRank | References | Authors |
0.34 | 9 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Christian Sánchez-Sánchez | 1 | 7 | 5.65 |
| Leonid Sheremetov | 2 | 198 | 28.37 |