Feature Selection for Natural Language Call Routing Based on Self-Adaptive Genetic Algorithm

5th International Workshop on Mathematical Models and their Applications 2016

Koromyslova, A.^1 ; Semenkina, M.^1 ; Sergienko, R.^2

Reshetnev Siberian State Aerospace University, Krasnoyarsky rabochy avenue 31, Krasnoyarsk

660037, Russia^1

Ulm University, Lise-Meitner-Str. 9, Ulm

89081, Germany^2

关键词: Classification algorithm;    Dimensionality reduction;    Dimensionality reduction method;    Feature selection methods;    Natural language call routing;    Numerical results;    Self adaptive genetic algorithm;    Text classification;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/173/1/012008/pdf
DOI  :  10.1088/1757-899X/173/1/012008

来源: IOP

【 摘 要 】

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.