Many users turn to document retrieval systems (e.g. search engines) to seek answers to controversial questions. Answering such user queries usually require identifying responses within web documents, and aggregating the responses based on their different perspectives. Classical document retrieval systems fall short at delivering a set of direct and diverse responses to the users. Naturally, identifying such responses within a document is a natural language understanding task. In this paper, we examine the challenges of synthesizing such language understanding objectives with document retrieval, and study a new perspective-oriented document retrieval paradigm. We discuss and assess the inherent natural language understanding challenges in order to achieve the goal. Following the design challenges and principles, we demonstrate and evaluate a practical prototype pipeline system. We use the prototype system to conduct a user survey in order to assess the utility of our paradigm, as well as understanding the user information needs for controversial queries.
翻译:许多用户转向文件检索系统(例如搜索引擎),以寻找对有争议的问题的答案。回答这些用户的询问通常需要在网络文件中找到答案,并根据不同的观点汇总答复。古典文件检索系统在向用户提供一系列直接和多样的答复方面不足。自然,在文件内找到这类答复是一项自然的语言理解任务。在本文件中,我们研究了将此类语言理解目标与文件检索结合起来的挑战,并研究了一个新的面向视角的文件检索模式。我们讨论并评估了内在的自然语言理解挑战,以实现这一目标。根据设计挑战和原则,我们展示并评价了一个实用的原型编审系统。我们使用原型系统进行用户调查,以评估我们的范式的效用,并了解用户对有争议的查询的信息需求。