Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций
Конференция: 5th International Workshop on Mathematical Models and their Applications 2016, IWMMA 2016; Krasnoyarsk; Krasnoyarsk
Год издания: 2017
Идентификатор DOI: 10.1088/1757-899X/173/1/012008
Ключевые слова: Deep Neural Networks, feature extraction, genetic algorithms, natural language processing systems, nearest neighbor search, routing algorithms, text processing, classification algorithm, dimensionality reduction, Dimensionality reduction method, feature selection methods, natural language call routing, numerical results, Self adaptive genetic algorithm, text classification, Classification (of information)
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 resПоказать полностьюearch 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.
Журнал: IOP Conference Series: Materials Science and Engineering
Выпуск журнала: 173
Номера страниц: 012008
Издатель: Institute of Physics Publishing