  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.
