MEMEN: Multi-layer Embedding with Memory Networks for Machine Comprehension

Understand

Machine comprehension(MC) style question answering is a representative problem in natural language processing.

• Previous methods rarely spend time on the improvement of encoding layer, especially the embedding of syntactic information and name entity of the words, which are very crucial to the quality of encoding.
• Moreover, existing attention methods represent each query word as a vector or use a single vector to represent the whole query sentence, neither of them can handle the proper weight of the key words in query sentence.
• In this paper, we introduce a novel neural network architecture called Multi-layer Embedding with Memory Network(MEMEN) for machine reading task.