Development of Question Answering Techologies on Large-Scale Text

大规模文本问答（QA）是指通过参考存储的大规模文本来回答用户提出的任何问题的技术。它使用户能够在考虑到问题中表达的兴趣和观点的情况下获得必要的信息。我们的研究旨在发展问答技术，使之成为一种以用户为中心的先进的信息获取手段，并取得了以下成果：第一，研究了交互式回答一系列相关问题的问答技术，这将取代目前针对孤立问题的问答技术。假设这种技术有助于报告的撰写，我们研究了那里提出了什么样的问题，以及回答这些问题需要什么程序。根据测试结果，我们设计了一个新的任务来测量有用的互动问答的能力，并构建了该任务的测试集。通过对本课题的技术现状的分析，我们发现在处理这些问题上还有很大的空间，在处理列表型问题时也存在一些理论上的问题。列表型问题要求系统枚举所有且只有正确的答案。其次，将可视化模式（如图表的使用）引入到当前基于文本的问答系统中。在这一部分的研究中，我们表明，适当的使用图表是可能的，通过考虑用户的意图，并提出了一种方法，诱导这样的意图通过对话。我们将多模态问答技术向前推进，提出了一个新的研究课题“趋势信息的摘要与可视化”，该课题涵盖了文本摘要、信息可视化和问答等领域。提出了一个框架的研究，我们构建了一个数据集的研究，其中包括一个语料库的语义注释的报纸文章的原始设计的编码系统有用的总结和可视化。

Question Answering (QA) on large-scale text is technology for answering any question from users by referring to stored large-scale text. It allows users to obtain the necessary information itself with consideration of the interest and perspective expressed in their questions. Our research aims at to develop QA and to establish it as a sophisticated user-centered information access means, and achieved the following results.First, QA technologies for answering series of related questions interactively were examined, which would replace the current QA technologies for isolated questions. Assuming that such a technology helps report writing, we examined what kind of questions are made there and what procedures are needed for answering those questions. Based on the findings of the examination, we designed a novel task for measuring the abilities useful for interactive QA has been and constructed a test set of that task. Analysis of the state-of-art technologies by this task revealed that we have still have a large room to handling those situations, and some theoretical problems remain in handling list-type questions, which request systems to enumerate all and only correct answers.Second, incorporating a visual mode such as usage of charts into the current text-based QA was examined. In this part of the research, we showed that an appropriate use of charts get possible by considering users' intention, and proposed a method for eliciting such an intention thorough dialogues. We pushed this multi-modal QA forward and proposed a novel research topic, "summarization and visualization on trend information", that covers the fields of text summarization, information visualization and QA. Presenting a framework of research, we constructed a data set for the research, which includes a corpus of semantically annotated newspaper articles of an originally designed coding system useful to summarization and visualization.