Determining the job is suitable for a student or a person looking for work
based on their job's descriptions such as knowledge and skills that are
difficult, as well as how employers must find ways to choose the candidates
that match the job they require. In this paper, we focus on studying the job
prediction using different deep neural network models including TextCNN,
Bi-GRU-LSTM-CNN, and Bi-GRU-CNN with various pre-trained word embeddings on the
IT Job dataset. In addition, we also proposed a simple and effective ensemble
model combining different deep neural network models. The experimental results
illustrated that our proposed ensemble model achieved the highest result with
an F1 score of 72.71%. Moreover, we analyze these experimental results to have
insights about this problem to find better solutions in the future.

本文通过使用不同的深度神经网络模型，包括 TextCNN、Bi-GRU-LSTM-CNN 和 Bi-GRU-CNN 以及各种预训练的单词嵌入来研究职业预测。此外，我们还提出了一个简单有效的组合模型。实验结果表明，我们的提出的组合模型取得了最高的 F1 分数为 72.71％。