Application of the Multi-label Residual Convolutional Neural Network text classifier using Content-Based Routing process
This is an incremental application of existing methods to a domain-specific problem in legal ad classification.
The paper tackles the problem of predicting events from legal ad text using a multi-label residual convolutional neural network for text classification, achieving unspecified results.
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.