Development of an universal open-domain question answering System that can give an answer to any type of real-world questions

本研究的目的是开发一个通用的开放域问题查询系统（UQA），它可以对任何类型的真实世界的问题返回一个答案。首先，为了了解在真实的世界中有多少种问题被提交，我们收集了Web上的问题和答案对，并对它们进行了详细的分析。我们调查了一个WWW问题门户社区网站，其中一个用户向Web站点提交问题，另一个看到问题的用户可以提交问题的答案。我们从网站上收集了1，187，873对，每一对都由一个问题和一组答案组成。然后，我们分析了从网站中随机抽取的2，064个问答对，并标注了答案类型。接下来，我们开始使用分析结果开发UQA系统。我们认为一个问题的正确答案满足以下两个命题：（1）它与它的问题共享相同的主题，（2）它具有与它的问题所期望的相同的答案类型。根据这一思想，我们实现的机制，分别测量两个命题，然后合并它们的结果，给每个答案候选人的可能性。开发的系统进行了评估，使用QAC 4测试收集，这已经建立在NTCIR-6研讨会在2006年开始评估非事实性问题回答。我们还进行了实验评估，发现从网站上收集的现实世界的问题的答案。实验结果表明，对于测量命题（2），单分类器方法是有效的，该方法通过使用检测来自问题侧的类型和来自答案侧的类型是否匹配的分类器来评估匹配。

This research aims at developing an Universal Open-domain Question Answering (UQA) System, which returns an answer for any type of real-world questions.First of all, in order to see how many kinds of questions are submitted in the real world, we collected pairs of question and answers in the Web and analyzed them in detail. We investigated one of the WWW question portal community sites, where a user submits a questions to the Web site and another user who see the question can submits the answer of the question. We collected 1,187,873 pairs, each of which consist of a question and a set of its answers, from the Web site. Then, we analyzed 2,064 question-answer pairs selected randomly from the site and annotated the answer types.Next, we started to develop an UQA system by using the result of the analysis. We consider that the correct answer of a question fulfills the following two propositions: (1) it shares the same topic with its question, (2) it has the same answer type as that expected by its question. According to this idea, we implemented the mechanisms that measures the two propositions separately, and then merges their results to give the likelihood to each answer candidates.The developed system was evaluated by using QAC4 test collection, which has been constructed at NTCIR-6 workshop started in 2006 for evaluating the non-factoid question answering. We also conducted the experimental evaluation of finding the answer of real-world questions collected from the Web site. The experimental result showed that, for measuring the proposition (2), the one-classifier approach was effective, which evaluate the matching by using a classifier that detects whether the type from the question side and the type from the answer side match or not.