Nanoblog processing

纳米博客处理

• 批准号: RGPIN-2021-02599
• 负责人: Khoury, Richard
• 金额: $ 2.55万
• 依托单位: Université Laval
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=742101
• 关键词: Nanoblog; processing

Natural Language Processing (NLP) has traditionally been done with long documents, and tasks with such documents achieve very high performances and many are even considered "solved". The popularity of SMS messaging and the creation of social networks led to the popularization of short text messages or "microblogs", and many previously-solved NLP tasks became open challenges again. New difficulties stemmed from the short length of the messages, the limited contextual information available, the use of unconventional language, and the socially-linked and dynamic nature of the conversations. Nevertheless, after a decade of research work, many of these challenges have been overcome and microblog-processing systems routinely achieve performances comparable to those in traditional NLP. And thanks to these advances, microblogs have become a valuable resource in other research areas as well. The next frontier in NLP will come from increasingly-popular in-game chat messages found in online games and gaming communities. These messages amplify the problems of microblogs: they are even shorter, consisting of sometimes only a single word or acronym and completely devoid of in-message context, they use language tailored to the specific game they are linked to and that is gibberish outside of that game, and only make sense as live conversations during a game. Due to their extremely short nature, we call these conversations "nanoblogs". The long-term objective of this research proposal is to pioneer the area of nanoblog NLP and ensure Canada's leadership in this emerging research area. To achieve this, we have defined three short-term research objectives to accomplish over the next five years. Objective 1: We will design, construct, and label a real-world nanoblog corpus. Objective 2: We will create nanoblog context modelling, normalization, and language detection algorithms. Objective 3: We will create nanoblog cyber-bullying filter algorithms.

自然语言处理（NLP）传统上是通过长文档来完成的，使用此类文档的任务可以获得非常高的性能，许多任务甚至被认为“已解决”。短信的普及和社交网络的创建导致了短信或“微博”的普及，许多以前解决的 NLP 任务再次成为公开的挑战。新的困难源于消息的长度短、可用的上下文信息有限、非常规语言的使用以及对话的社会联系和动态性质。然而，经过十年的研究工作，许多挑战已经被克服，微博处理系统通常可以达到与传统 NLP 相当的性能。由于这些进步，微博也已成为其他研究领域的宝贵资源。 NLP 的下一个前沿将来自在线游戏和游戏社区中日益流行的游戏内聊天消息。这些消息放大了微博的问题：它们甚至更短，有时仅由单个单词或缩写词组成，并且完全没有消息内上下文，它们使用针对所链接的特定游戏量身定制的语言，除此之外就是胡言乱语。游戏，并且只有在游戏期间的实时对话才有意义。由于其极其简短的性质，我们将这些对话称为“纳米博客”。 该研究计划的长期目标是开拓纳米博客 NLP 领域，并确保加拿大在这一新兴研究领域的领导地位。为了实现这一目标，我们确定了未来五年要完成的三个短期研究目标。目标 1：我们将设计、构建和标记一个真实世界的纳米博客语料库。目标 2：我们将创建纳米博客上下文建模、标准化和语言检测算法。目标 3：我们将创建纳米博客网络欺凌过滤算法。