Open AccessComplaint Classification using Word2Vec Model
Author(s) -
Mohit Rathore,
Dikshant Gupta,
Dinabandhu Bhandari
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i4.5.20192
Subject(s) - word2vec , complaint , artificial intelligence , computer science , classifier (uml) , recurrent neural network , perceptron , machine learning , pattern recognition (psychology) , artificial neural network , embedding , political science , law
Attempt has been made to develop a versatile, universal complaint grievance segregator by classifying orally acknowledged grievancesinto one of the predefined categories. The oral complaints are first converted to text and then each word is represented by a vector usingword2vec. Each grievance is represented by a single vector using Gated Recurrent Unit (GRU) that implements the hidden state of Recurrent Neural Network (RNN) model. The popular Multi-Layer Perceptron (MLP) has been used as the classifier to identify the categories.