III: Small: Active Learning of Language Models for Information Extraction

该项目研究从Web上提取准确的知识库的方法。全自动Web信息提取技术具有大规模可伸缩性，但存在准确性和覆盖面限制。这项提案调查了如何通过引入精心挑选的人工指导来改进自动提取技术。该系统不断地从Web上提取知识，同时动态合成并向人类发出查询，以提高系统知识库和抽取器的准确性，该方法扩展了PI先前利用统计语言模型(SLM)进行信息提取的工作。为了将Web表格中表示的关系数据的提取与从自由文本中的提取统一起来，研究了新的SLM。新的主动学习技术利用这些模型来识别“高杠杆”的查询--例如，请求文本提取模式，当从Web上检索时，这些模式会产生数千个新的提取。被调查的查询大多是非专家的，这意味着大部分人工输入可以通过在线大规模协作来大规模获取。该项目的更广泛影响在于，准确的Web提取可能从根本上改进Web搜索，允许用户通过合成多个Web页面的信息来回答复杂的问题。在医学和生物等领域，挖掘提取的知识库可以产生重要的发现和新的治疗方法。更多信息可以在项目Web page:http://wail.eecs.northwestern.edu/projects/activelms/index.html中找到

This project studies methods for extracting accurate knowledge bases from the Web. Fully-automated Web information extraction techniques are massively scalable, but have accuracy and coverage limitations. This proposal investigates how to improve automated extraction techniques by introducing carefully-selected human guidance. The proposed system continually extracts knowledge from the Web, along the way dynamically synthesizing and issuing queries to humans to increase the accuracy of the system's knowledge base and extractors.The approach extends the PI's previous work utilizing statistical language models (SLMs) for information extraction. Novel SLMs are investigated for unifying the extraction of relational data expressed in Web tables with extraction from free text. New active learning techniques utilize the models to identify "high-leverage" queries -- requesting, for example, textual extraction patterns that when retrieved from the Web yield thousands of novel extractions. The queries investigated are mostly amenable to non-experts, meaning that much of the human input can be acquired at scale via online mass-collaboration.The broader impact of this project lies in the potential for accurate Web extraction to radically improve Web search, allowing users to answer complicated questions by synthesizing information across multiple Web pages. In domains like medicine and biology, mining extracted knowledge bases could lead to important discoveries and novel therapies.Further information may be found at the project web page:http://wail.eecs.northwestern.edu/projects/activelms/index.html