English

Application of the Multi-label Residual Convolutional Neural Network text classifier using Content-Based Routing process

Computation and Language 2022-10-03 v3 Artificial Intelligence Machine Learning

Abstract

In this article, we will present an NLP application in text classifying process using the content-based router. The ultimate goal throughout this article is to predict the event described by a legal ad from the plain text of the ad. This problem is purely a supervised problem that will involve the use of NLP techniques and conventional modeling methodologies through the use of the Multi-label Residual Convolutional Neural Network for text classification. We will explain the approach put in place to solve the problem of classified ads, the difficulties encountered and the experimental results.

Keywords

Cite

@article{arxiv.2110.15801,
  title  = {Application of the Multi-label Residual Convolutional Neural Network text classifier using Content-Based Routing process},
  author = {Tounsi Achraf and Elkefi Safa},
  journal= {arXiv preprint arXiv:2110.15801},
  year   = {2022}
}

Comments

The paper has mistakes technically

R2 v1 2026-06-24T07:17:50.941Z