Библиографическое описание:Feature Selection for Natural Language Call Routing Based on Self-Adaptive Genetic Algorithm : доклад, тезисы доклада / A. Koromyslova, M. E. Semenkina, R. Sergienko. - [S. l. : s. n.], 2017. - Текст : непосредственный // IOP Conference Series: Materials Science and Engineering : 5th International Workshop on Mathematical Models and their Applications 2016, IWMMA 2016 : Institute of Physics Publishing, 2017. - 173. - P. 012008. - DOI 10.1088/1757-899X/173/1/012008.
Аннотация:The text classification problem for natural language call routing was considered in the paper. Seven different term weighting methods were applied. As dimensionality reduction methods, the feature selection based on self-adaptive GA is considered. k-NN, linear SVM and ANN were used as classification algorithms. The tasks of the research are the following: perform research of text classification for natural language call routing with different term weighting methods and classification algorithms and investigate the feature selection method based on self-adaptive GA. The numerical results showed that the most effective term weighting is TRR. The most effective classification algorithm is ANN. Feature selection with self-adaptive GA provides improvement of classification effectiveness and significant dimensionality reduction with all term weighting methods and with all classification algorithms.
