Complaint Classification using Word2Vec Model

  • Authors

    • Mohit Rathore
    • Dikshant Gupta
    • Dinabandhu Bhandari
    2018-09-22
    https://doi.org/10.14419/ijet.v7i4.5.20192
  • Gated Recurrent Unit, Recurrent Neural Network, Text Classification, Word2Vec

  • Abstract

    Attempt has been made to develop a versatile, universal complaint grievance segregator by classifying orally acknowledged grievances

    into one of the predefined categories. The oral complaints are first converted to text and then each word is represented by a vector using

    word2vec. 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.

     

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  • How to Cite

    Rathore, M., Gupta, D., & Bhandari, D. (2018). Complaint Classification using Word2Vec Model. International Journal of Engineering & Technology, 7(4.5), 402-404. https://doi.org/10.14419/ijet.v7i4.5.20192

    Received date: 2018-09-24

    Accepted date: 2018-09-24

    Published date: 2018-09-22