Recurrent Neural Network for Storytelling
YunSeok Choi, Suah Kim, Jee-Hyong Lee · 2016
Storytelling is the act of passing on what you want to tell other people as so interesting and true-to-life story. As the study in text mining progresses to express words, sentences and paragraphs as vector, it is possible to classify text and generate text using vectors. However, it has not much progressed to generate a correct flow of context and a correct grammar of context in text mining. In this paper, we propose first neural network model that learn one sentence and one vector is mapped for representing vectors as sentences. And we propose second neural network model that learn the contents of stories for generating sentences. Finally we evaluate the proposed model can generate sentences having stories than other method using ROUGE.