  Knowledge bases (KBs) have attracted increasing attention due to its great
success in various areas, such as Web and mobile search.Existing KBs are
restricted to objective factual knowledge, such as city population or fruit
shape, whereas,subjective knowledge, such as big city, which is commonly
mentioned in Web and mobile queries, has been neglected. Subjective knowledge
differs from objective knowledge in that it has no documented or observed
ground truth. Instead, the truth relies on people's dominant opinion. Thus, we
can use the crowdsourcing technique to get opinion from the crowd. In our work,
we propose a system, called crowdsourced subjective knowledge acquisition
(CoSKA),for subjective knowledge acquisition powered by crowdsourcing and
existing KBs. The acquired knowledge can be used to enrich existing KBs in the
subjective dimension which bridges the gap between existing objective knowledge
and subjective queries.The main challenge of CoSKA is the conflict between
large scale knowledge facts and limited crowdsourcing resource. To address this
challenge, in this work, we define knowledge inference rules and then select
the seed knowledge judiciously for crowdsourcing to maximize the inference
power under the resource constraint. Our experimental results on real knowledge
base and crowdsourcing platform verify the effectiveness of CoSKA system.
