Indicative Summarization of Fiction

Wattpad是一个社交平台，托管用户上传的小说集供他人阅读。它现在有 收集了超过5000万个故事，每月拥有超过4000万用户。一个重大问题 该公司在改进其平台时面临的一个问题是，它需要为用户提供一种方法， 收藏中的兴趣。该项目旨在开发生成故事摘要的方法， 以帮助用户决定它们是否值得阅读。这是自然语言中的一个研究问题 处理（NLP），并将涉及开发技术，以了解在某种程度上的故事结构 (e.g.,背景、人物、体裁或情节），决定与潜在读者相关的信息，然后 用文字表达出来。我们计划使用语言理解的概率方法来调查这些问题 和从故事和伴随的摘要的语料库中学习的一代。这项研究的结果 通过帮助这家加拿大公司提供一个更具吸引力的平台， 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.