Microtext Processing

术语“微文本”描述了一种非常短（通常是一句话或更少）的文本文档，以非正式的方式编写，并且未经编辑以保证质量，并且包括一些元数据。微文本在当今世界已经无处不在，包括在线用户评论，Facebook新闻源和推文以及搜索查询。就其本质而言，微文本是一个与传统自然语言处理（NLP）非常不同的挑战。它们的短长度阻碍了依赖词频和统计数据的NLP方法，并且大量的拼写错误，错别字和非常规缩写使标准语言资源毫无帮助。缩微文本处理应该被看作是自然语言处理的一个新的分支。第一个目标是开发专门的查询理解和回答使用企业知识库的任务的微文本理解算法。第二个目标是开发专门用于Twitter中非常精确的事件检测任务的微文本理解算法。第三个目标是开发专门用于挖掘微博讨论任务的微文本理解算法，特别是在检索软件开发信息的背景下。第四个目标是开发一个“军事沃森”，可以监控军事聊天，并通知军官发生的重要国际事件。所有四个项目都是与外部研究和工业伙伴合作完成的。此外，它们都是为了一个统一的长期目标：开拓和开发缩微文本处理的新领域，并创建缩微文本专业知识的核心。微文本处理的发展将是语义网和Web 2.0发展的下一个重要里程碑。今天产生的微文本数量绝对是巨大的：例如，每天在Google上有47亿次网络查询和3.4亿条推文。网络用户积极寻求并接受新的缩微文本技术。这项研究对加拿大经济的战略重要性怎么强调都不过分，我们的多个合作伙伴公司和组织将直接受益于我们的研究结果。

The term "microtext" describes a type of text document that is very short (typically one sentence or less), is written in an informal manner and unedited for quality, and includes some metadata. Microtexts have become omnipresent in today's world, and include online user comments, Facebook newsfeeds and Tweets, and search queries. By their very nature, microtexts are a very different challenge from traditional Natural Language Processing (NLP). Their short length hinders NLP methodologies that rely on word frequencies and statistics, and the abundance of spelling mistakes, typos, and unconventional abbreviations make standard linguistic resources unhelpful. Microtext processing should be seen as a new branch of NLP.This proposal brings together four parallel five-year microtext research programs. The first aims to develop microtext understanding algorithms specialized to the task of query understanding and answering using corporate knowledge bases. The second aims to develop microtext understanding algorithms specialized to the task of very precise event detection in Twitter. The third aims to develop microtext understanding algorithms specialized to the task of mining microblog discussions, specifically in the context of retrieving software development information. And the fourth aims to develop a "military Watson" that can monitor military chat and inform officers of crucial international events occurring. All four projects are done in collaboration with external research and industrial partners. Moreover, they all feed into a single unifying long-term objective: to pioneer and develop the new field of microtext processing, and create a core of microtext expertise. The development of microtext processing will be the next major milestone in Semantic Web and Web 2.0 development. The amount of microtext generated today is absolutely massive: for example, there are 4.7 billion web queries asked on Google and 340 million Tweets posted every day. Web users actively seek out and embrace new microtext technology. The strategic importance of this research for the Canadian economy cannot be overstated, and our multiple partner companies and organizations will benefit directly from our results.