Learning to Recommend Quotes for Writing

In this paper, we propose and address a novel task of recommending quotes for writing. Quote is short for quotation, which is the repetition of someone else’s statement or thoughts. It is a common case in our writ-ing when we would like to cite someone’s statement, like a proverb or a statement by some famous people, to make our composition more elegant or convincing. However, sometimes we are so eager to make a cita-tion of quote somewhere, but have no idea about the relevant quote to express our idea. Because knowing or remembering so many quotes is not easy, it is exciting to have a system to recommend relevant quotes for us while writing. In this paper we tackle this appealing AI task, and build up a learning framework for quote rec-ommendation. We collect abundant quotes from the In-ternet, and mine real contexts containing these quotes from large amount of electronic books, to build up a dataset for experiments. We explore the particular fea-tures of this task, and propose a few useful features to model the characteristics of quotes and the relevance of quotes to contexts. We apply a supervised learning to rank model to integrate multiple features. Experiment results show that, our proposed approach is appropriate for this task and it outperforms other recommendation methods