  This paper proposes a new task in the field of Answering Subjective Induction
Question on Products (SUBJPQA). The answer to this kind of question is
non-unique, but can be interpreted from many perspectives. For example, the
answer to 'whether the phone is heavy' has a variety of different viewpoints. A
satisfied answer should be able to summarize these subjective opinions from
multiple sources and provide objective knowledge, such as the weight of a
phone. That is quite different from the traditional QA task, in which the
answer to a factoid question is unique and can be found from a single data
source. To address this new task, we propose a three-steps method. We first
retrieve all answer-related clues from multiple knowledge sources on facts and
opinions. The implicit commonsense facts are also collected to supplement the
necessary but missing contexts. We then capture their relevance with the
questions by interactive attention. Next, we design a reinforcement-based
summarizer to aggregate all these knowledgeable clues. Based on a
template-controlled decoder, we can output a comprehensive and
multi-perspective answer. Due to the lack of a relevant evaluated benchmark set
for the new task, we construct a large-scale dataset, named SupQA, consisting
of 48,352 samples across 15 product domains. Evaluation results show the
effectiveness of our approach.
