RI: Small: Acquiring Domain Knowledge from Text through Cooperative Bootstrapping

自然语言处理（NLP）技术的一些最迫切的需求来自于广泛覆盖解决方案不足的专业领域，例如临床医学和分子生物学。 该项目的重点是开发自举学习技术，以快速创建特定领域的语义分析器，该项目建立了一种新的协作自举范式，通过允许不同任务的分类器相互学习，同时学习不同任务的语义分析器，然后这些分析器将提取的语义信息填充到领域事件图中从特定于域的文本集合中。新的知识收获算法从图中获取特定领域的事实和推理规则。本项目通过兽医在留言板上发布的信息来获取动物健康监测所需的真实知识，从而探索兽医学领域。本项目将通过开发新的自举框架来快速创建专门领域的语义分析工具，从而推进自然语言技术的最新发展。 这项技术将影响许多NLP应用，包括信息提取、问答和摘要。 知识收集工具将公开提供，以便对需要从非结构化文本集合中提取知识的许多学科产生直接影响。 该项目还将为动物健康监测创造新的工具，为动物传染病爆发（如禽流感和疯牛病）、接触有毒物质和食物链污染提供早期预警信号，从而造福社会。

Some of the most pressing needs for natural language processing (NLP) technology come from specialized domains where broad-coverage solutions are not sufficient, such as clinical medicine and molecular biology. This project focuses on the development of bootstrapped learning techniques to rapidly create domain-specific semantic analyzers, and the automatic harvesting of domain knowledge from unstructured text.This project establishes a new cooperative bootstrapping paradigm to learn semantic analyzers for different tasks simultaneously by allowing classifiers for different tasks to learn from each other.These analyzers then populate a domain event graph with semantic information extracted from a domain-specific text collection. New knowledge harvesting algorithms acquire domain-specific facts and inference rules from the graph. This project explores the domain of veterinary medicine using message board posts by veterinarians to acquire real-world knowledge for the purposes of animal health surveillance.This work will advance the state-of-the-art in natural language technology by developing a new bootstrapping framework to rapidly create semantic analysis tools for specialized domains. This technology will impact many NLP applications, including information extraction, question answering, and summarization. The knowledge harvesting tools will be made publicly available to allow for direct impact across many disciplines that have a need to extract knowledge from unstructured text collections. This project will also benefit society by creating new tools for animal health surveillance, which could provide early warning signs of zoonotic disease outbreaks (such as bird flu and mad cow disease), exposures to toxic substances, and contamination in the food chain.