Using technologies to support investigative interviewers in detecting deception

使用技术支持调查访谈员发现欺骗行为

• 批准号: 1955087
• 金额: --
• 依托单位: University of Sussex
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2016
• 资助国家: 英国
• 起止时间: 2016 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-1955087
• 关键词: Using; technologies; support; investigative; interviewers

The project explores how investigative interviews (e.g., police, immigration, HMRC, benefits, etc.) can be facilitated by the provision of technological support. This support takes the form of a user interface that displays factoids relevant to the current stage of the interview, for example the name of a person the interviewee should know. These factoids are extracted from knowledge bases such as Wikipedia and also from the Web sites of relevant organisations. This Web Information Extraction is the key topic of this research. The challenge is to perform Named Entity Recognition and Co-reference Resolution on a whole Web site, taking into account the richer information present on the Web, such as formatting, position, titles and headings. These extracted entities for each Web page are then integrated to form an entity graph for the whole Web site that can be consumed by the user interface. A semi-supervised approach to training direct on HTML is proposed, guided by a lexicon extracted from Wikipedia.

该项目探讨了调查性采访（例如，警察，移民，HMRC，福利等）可以通过提供技术支持来促进。这种支持采取用户界面的形式，显示与访谈当前阶段相关的事实，例如受访者应该知道的人的姓名。这些虚假事实是从维基百科等知识库以及相关组织的网站中提取的。Web信息抽取是本文研究的重点。挑战是在整个网站上执行命名实体识别和共指解析，同时考虑到Web上存在的更丰富的信息，例如格式，位置，标题和标题。然后，将每个Web页面的这些提取的实体进行集成，以形成可以由用户界面使用的整个Web站点的实体图。提出了一种直接在HTML上训练的半监督方法，该方法由从维基百科中提取的词典指导。

项目成果

Leveraging HTML in Free Text Web Named Entity Recognition

• DOI: 10.18653/v1/2020.coling-main.36
• 发表时间: 2020-12
• 作者: Colin Ashby;David Weir