基于CNN和注意机制的开放域文档自动QA模型

Guangjie Zhang, Xumin Fan, Canghong Jin, Ming-hui Wu
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引用次数: 3

摘要

近年来,开放域自动问答模型得到了广泛的研究。在处理自动问答系统时,基于rnn的模型是最常用的模型。然而,我们选择基于cnn的模型来构建我们的问答模型,并使用注意机制来提高性能。我们在Microsoft开放域自动问答数据集上测试了我们的模型。实验表明,与没有注意机制的模型相比,我们的模型得到了最好的结果。实验还表明,在我们的模型中加入RNN网络可以进一步提高性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Open-Domain Document-Based Automatic QA Models Based on CNN and Attention Mechanism
The open domain automatic question answering models have been widely studied in recent years. When dealing with automatic question answering systems, the RNN-based models are the most commonly used models. However we choose the CNN-based model to construct our question answering models, and use the attention mechanism to enhance the performance. We test our models on Microsoft open domain automatic question answering dataset. Experiments show that compared with the models without attention mechanism, our models get the best results. Experiments also show that adding the RNN network in our model can further improve the performance.
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