产生连贯的叙事与子主题规划,以回答如何的问题
Pengshan Cai1, Mo Yu2, Fei Liu3
1Manning College of Information & Computer Sciences, University of Massachusetts, Amherst.
概括
对于如何回答的问题来说,生成长形式的答案是具有挑战性的. 这项研究引入了一种新的架构与子主题规划,以创建连贯的,多样化的叙述,改善复杂查询的答案质量.
科学领域:
- 自然语言处理自然语言处理.
- 人工智能的人工智能
背景情况:
- 回答如何问题是回答问题 (QA) 中的一个重大挑战.
- 许多狭窄,长尾的教程问题没有得到传统搜索引擎的良好服务.
- 对于培训系统来回答这些类型的问题,存在有限的注释数据.
研究的目的:
- 开发一种新的架构,用于生成连贯的,长篇的答案如何问题.
- 为了解决这个特定的质量保证任务缺乏注释数据的问题.
- 提高产生的答案的质量和多样性.
主要方法:
- 提出了一个新的架构,包括段落检索,子主题规划和叙事生成.
- 实现了一个子话题规划模块,以创建各种各样的子话题,以构建答案.
- 将多个相关段落整合到一个单一,连贯,解释性的答案中.
主要成果:
- 证明了为如何问题生成高质量的叙述的困难.
- 展示了拟议的架构与子主题规划产生了更好的答案质量.
- 使用自动指标和人类评估评估生成的叙述,确认多样性和质量.
结论:
- 为如何问题生成长形式的答案是一个复杂但可以实现的任务.
- 在叙事生成中,子话题规划对于提高话题连贯性和答案质量至关重要.
- 拟议的架构提供了一种有希望的方法来解决长尾如何回答问题的问题.
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