Enhancing unsupervised neural networks based text summarization with word embedding and ensemble learning

作者：

Highlights：

• Word2vec representation improves the summarization task compared to bag of words.

• Feature learning using unsupervised neural networks improves the summarization task.

• Unsupervised neural networks trained on word2vec vectors gives promising results.

• Ensemble learning with word2vec representation obtains the best results.

摘要

•Word2vec representation improves the summarization task compared to bag of words.•Feature learning using unsupervised neural networks improves the summarization task.•Unsupervised neural networks trained on word2vec vectors gives promising results.•Ensemble learning with word2vec representation obtains the best results.

论文关键词：Text summarization,Neural networks,Word2vec,Auto-encoder,Variational auto-encoder,Extreme learning machine

论文评审过程：Received 2 June 2018, Revised 9 January 2019, Accepted 10 January 2019, Available online 11 January 2019, Version of Record 19 January 2019.

论文官网地址：https://doi.org/10.1016/j.eswa.2019.01.037