[2H6-GS-9] Natural language processing, information retrieval: Document generation

[2H6-GS-9-03] Response Document Generation for Accommodation Reviews Using Hierarchical Encoder-Decoder Models

〇Yuriko Hashizume¹, Mikio Yamamoto¹ (1. Graduate school of System and Information Engineering, University of Tsukuba)

Keywords:Deep Learning, language generation, sequence-to-sequence, attention

We examine a system for presenting the draft text to writers of response documents. Since a document is a set of sentences, it is necessary to handle a symbol sequence longer than a sentence conversion such as a conventional machine translation. We propose a method using pre-trained sentence embedding as input of hierarchical RNN encoder-decoder model. It can generate a more detailed response document than the simple non-hierarchical RNN encoder-decoder model.