Visual text analytics for total recall information retrieval in large noisy text datasets

在海量文本语料库中找到感兴趣信息的搜索范例已经很好地建立起来，网络搜索引擎的成功就是一个例证。下一个前沿是由领域专家和分析师支持从中大规模文本语料库中进行意义构建，他们试图挖掘隐藏在文本中的隐性知识。与Web搜索不同，Web搜索通过几个高质量的结果来满足用户的信息需求，而领域分析人员通常需要查找与感兴趣的主题相关的所有文档。此外，领域分析人员的信息需求通常过于复杂，难以用少量的查询术语来表示。这些要求与网络搜索引擎的要求非常不同。该项目的目标是在具有重大实际意义的使用案例的背景下，制定满足这些要求的算法和系统，这些案例包括：关于工厂工人事件和航空事件的报告；普通法法律制度中的法院裁决；用于系统审查的医学研究文献；以及现有技术专利检索。主要挑战包括：词汇不匹配，用户查询的词汇与相关文件中使用的词汇不同；设计互动机制和可视化，以支持互动性质，并将人工反馈纳入检索过程。拟议研究的影响将是改善记录和研究事故的各种领域的安全，以获得关于如何防止未来事故的见解，如工厂、航空、医院和养老院。

The search paradigm for finding information of interest in massive text corpora is well established, and exemplified by the success of Web search engines. The next frontier is the support of sense-making out of medium to large scale text corpora by the domain expert and analyst, who is trying to untap the tacit knowledge hidden in the text. In contrast to Web search, where the user's information need is satisfied by a few high-quality results, the domain analyst typically needs to find all relevant documents related to a topic of interest. Furthermore the domain analyst's information need is often much too complex to be easy to express in a small number of query terms. These requirements are very different from those of a web search engine. This project aims towards algorithms and systems that will address such requirements, in the context of use cases of significant practical interest including: reports on factory worker incidents and on aviation incidents; court decisions in the common law legal system; medical research literature for generation of systematic reviews; and prior art patent search. Key challenges include: vocabulary mismatch, where the queries of the user contain a vocabulary that is different from that used in the relevant documents; design of interactive mechanisms and visualizations to support the interactive nature of and incorporate human feedback into the retrieval process. The impact of the proposed research will be improvement of safety in a variety of domains where incidents are recorded and studied to obtain insights on how to prevent future incidents, such as in factories, aviation, hospitals and old-age homes.