How an Autonomous Information Retrieval Agent Affects Divergent
Thinking by a Group
We have been developing a creativity support system called ``AIDE,''
which is equipped with various agents to stimulate creative group
conversations. In this paper, we describe an autonomous information
retrieval agent called ``Conversationalist,'' which is one of the
agents of AIDE and is responsible for stimulating human divergent
thinking. This agent analyzes the relationships among utterances and
the structure of the topic in a conversation, and autonomously
extracts various pieces of information relevant to the current
conversation. Furthermore, we also show subjective experiments of
AIDE applied to brainstorming sessions. From the results of the
experiments, we confirmed that the agent is effective in stimulating
human divergent thinking and in extracting more ideas from subjects,
than in brainstorming sessions without the agent. Based on the
results, we discuss what kind of information retrieval method is
effective and when extracted pieces of information should be provided.
Consequently, the following results are suggested: 1) when a
conversation is active, the frequency of information provision by the
agent should be rather low, and the relationship between the topic of
the conversation and the pieces of information should not be so far,
and 2) when a conversation is not active, i.e., is stagnate, or
asynchronously executed, the frequency of information provision by the
agent should be rather high, and the pieces of information should
include some hidden relations with the topic of the conversation.