Application of the Multi-label Residual Convolutional Neural Network text classifier using Content-Based Routing process
Year: 2021
Type: preprint
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.
Source: arXiv (Cornell University)
Authors: Achraf, Tounsi, Safa, Elkefi
Institution: Stevens Institute of Technology
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W3210614148