  Human computer conversation is regarded as one of the most difficult problems
in artificial intelligence. In this paper, we address one of its key
sub-problems, referred to as short text conversation, in which given a message
from human, the computer returns a reasonable response to the message. We
leverage the vast amount of short conversation data available on social media
to study the issue. We propose formalizing short text conversation as a search
problem at the first step, and employing state-of-the-art information retrieval
(IR) techniques to carry out the task. We investigate the significance as well
as the limitation of the IR approach. Our experiments demonstrate that the
retrieval-based model can make the system behave rather "intelligently", when
combined with a huge repository of conversation data from social media.
