This article introduces a n-gram-based approach to automatic classification of Web services using a multilayer perceptron-type artificial neural network. Web services contain information that is useful for achieving a classification based on its functionality. The approach relies on word n-grams extracted from the web service description to determine its membership in a category. The experimentation carried out shows promising results, achieving a classification with a measure F=0.995 using unigrams (2-grams) of words (characteristics composed of a lexical unit) and a TF-IDF weight.
| Identifer | oai:union.ndltd.org:PERUUPC/oai:repositorioacademico.upc.edu.pe:10757/652143 |
| Date | 07 January 2020 |
| Creators | Silva, Jesús, Senior Naveda, Alexa, Solórzano Movilla, José, Niebles Núẽz, William, Hernández Palma, Hugo |
| Publisher | Institute of Physics Publishing |
| Source Sets | Universidad Peruana de Ciencias Aplicadas (UPC) |
| Detected Language | English |
| Type | info:eu-repo/semantics/article |
| Format | application/pdf |
| Source | Journal of Physics: Conference Series, 1432, 1 |
| Rights | info:eu-repo/semantics/openAccess, Attribution-NonCommercial-ShareAlike 4.0 International, http://creativecommons.org/licenses/by-nc-sa/4.0/ |
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