Indicative Summarization of Fiction

Wattpad是一个社交平台，它托管着用户上传的小说集，供其他人阅读。它现在有了 收集了超过5000万个故事，每月有超过4000万的用户。一个重大问题 该公司在改进其平台时面临的问题是，它需要为用户提供一种查找故事的方式 收藏品中的利息。该项目旨在开发生成故事摘要的方法，在 以帮助用户决定它们是否值得阅读。这是一个自然语言的研究问题 处理(NLP)，并将涉及开发技术以在一定程度上理解故事的结构 (例如，背景、人物、流派或情节)，决定与潜在读者相关的信息，然后 用文字来表达这一点。我们计划使用语言理解的概率方法来研究这些问题 以及从故事语料库和伴随的摘要中学习的一代。这项研究的结果 可以帮助这家加拿大公司提供更具吸引力的平台，从而为其提供竞争优势 和产品。

Wattpad is a social platform that hosts collections of fiction uploaded by its users for others to read. It now has a collection of over 50 million stories, and has a membership of over 40 million monthly users. A major issue faced by the company in improving its platform is that it needs to provide a way for users to find stories of interest within the collection. This project aims to develop methods for generating summaries of the stories, in order to help users decide whether they are worth reading. This is a research problem in natural language processing (NLP), and will involve developing techniques to understand the structure of the story at some level (e.g., the setting, characters, genre, or plot), decide on the information relevant to a potential reader, and then express that in text. We plan to investigate these issues using probabilistic methods of language understanding and generation that learn from a corpus of stories and accompanying abstracts. The outcomes of this research could provide a competitive advantage to this Canadian company by helping it offer a more attractive platform and product.