Determine if a piece of text is a job ad

For text classification in your case, it can be solved by training a binary classes classification network. Main steps as follows:

1. Training data preparation

Two classes data are needed, one class contain job ad text, and the other does not contain job ad.

2. Building the network

Building a binary classification network with Keras, Caffe or any other DL library you like.

3. Train the network

Training the network on the data prepared above.

4. Text class prediction

Use the trained network to predict the text class you want to deal with.

It’s a easy classification task for neural network: )

In case the con(text) is not too complex, you will not necessarily need a neural net to classify the text. Often a simple „bag of words“ with a ridge regression will do the job. This is more efficient (less code, less tuning).

Find a minimal example of (binary) text classification here: https://github.com/Bixi81/R-ml/blob/master/NLP_regression_bag_of_words.R