Automatic poetry analysis is usually examined as subtask of natural language processing but approaches which are good for prose texts are ineffective for poetry due to free semantic characteristics. It allows us to use large corpus for training words order and rather small text corpus amount. In this paper we suggest the way to adapt poetry texts to prose ones by changing word order without loosing of model and also use word2vec features to improve the classifier work.
|Journal||Journal of Physics: Conference Series|
|Publication status||Published - 4 Dec 2019|
|Event||2019 Big Data and Artificial Intelligence Conference - Moscow, Russian Federation|
Duration: 18 Sep 2019 → 19 Sep 2019