An Information Retrieval Approach to Short Text Conversation
This addresses the sub-problem of short text conversation in human-computer interaction, but it is incremental as it applies existing IR techniques to a new domain.
The authors tackled the problem of generating responses in short text conversations by formalizing it as an information retrieval task and using social media data, achieving intelligent system behavior with a retrieval-based model.
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.