Semantic Ideation Learning for Agent-Based e-Brainstorming

Abstract

Brainstorming has been a solution that helps organizations to generate creative ideas through teamwork and collaboration. However, by far, the role of information technology in brainstorming is merely like an assistant that passively supports the progression of brainstorming sessions instead of proactively engaging in the sessions. This research combines human`s unique association thinking with the intelligent agent technique, devising an automated decision agent called Semantic Ideation Learning Agent (SILA) that can represent a session participant to actively participate in brainstorming. SILAs are grounded on the three association capabilities of human`s thinking (similarity, contiguity, contrast). Moreover, a Collective Brainstorming Decision System (CBDS) is built to furnish an environment where SILAs can learn and share their knowledge with each other. We have successfully integrated CBDS into an intelligent care project (iCare) for the purpose of innovated e-service recommendation. The evaluation results are fairly promising.