Feature Selection for Natural Language Call Routing Based on Self-Adaptive Genetic Algorithm
نویسندگان
چکیده
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.
منابع مشابه
An Adaptive LEACH-based Clustering Algorithm for Wireless Sensor Networks
LEACH is the most popular clastering algorithm in Wireless Sensor Networks (WSNs). However, it has two main drawbacks, including random selection of cluster heads, and direct communication of cluster heads with the sink. This paper aims to introduce a new centralized cluster-based routing protocol named LEACH-AEC (LEACH with Adaptive Energy Consumption), which guarantees to generate balanced cl...
متن کاملA Random Forest Classifier based on Genetic Algorithm for Cardiovascular Diseases Diagnosis (RESEARCH NOTE)
Machine learning-based classification techniques provide support for the decision making process in the field of healthcare, especially in disease diagnosis, prognosis and screening. Healthcare datasets are voluminous in nature and their high dimensionality problem comprises in terms of slower learning rate and higher computational cost. Feature selection is expected to deal with the high dimen...
متن کاملFeature selection using genetic algorithm for breast cancer diagnosis: experiment on three different datasets
Objective(s): This study addresses feature selection for breast cancer diagnosis. The present process uses a wrapper approach using GA-based on feature selection and PS-classifier. The results of experiment show that the proposed model is comparable to the other models on Wisconsin breast cancer datasets. Materials and Methods: To evaluate effectiveness of proposed feature selection method, we ...
متن کاملDiscriminative Training and Support V Language Call Ro
In natural language call routing, callers are routed to desired departments based on natural spoken responses to an open-ended “How may I direct your call?” prompt. Natural language call classification can be performed using support vector machines (SVMs) or the popular vector-based model used in information retrieval. We recently demonstrate how discriminative training is powerful to improve a...
متن کاملA Parallel Genetic Algorithm Based Method for Feature Subset Selection in Intrusion Detection Systems
Intrusion detection systems are designed to provide security in computer networks, so that if the attacker crosses other security devices, they can detect and prevent the attack process. One of the most essential challenges in designing these systems is the so called curse of dimensionality. Therefore, in order to obtain satisfactory performance in these systems we have to take advantage of app...
متن کامل