Idea divergent editor using analogy: The IDEA system

Takashi Hayashi, Masafumi Hagiwara

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

In this article, an idea divergent editor using analogy (IDEA) system has been proposed. The analogies between two concepts are learned using a neural network through training. First, the problem that a user wants to solve is input to the proposed IDEA system. Second, the IDEA system can draw effective analogies from a knowledge base containing large-scale and wide-ranging concepts for solutions to various problems. The user chooses one of the analogies. Then, the IDEA system presents questions that prompt the user to analyze the problem with reference to the background of the analogy. Answering the presented questions triggers off an inspiration of a solution. The IDEA system facilitates users' divergent thinking, which creates many fragments of ideas. We performed an experiment to examine the effectiveness of the IDEA system; the number of ideas generated is increased about 1.5 ∼ 2.0 times using the IDEA system.

Original languageEnglish
Pages (from-to)1155-1172
Number of pages18
JournalInternational Journal of Intelligent Systems
Volume18
Issue number11
DOIs
Publication statusPublished - 2003 Nov

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Analogy
Neural networks
Experiments
Trigger
Knowledge Base
Fragment
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Neural Networks
Experiment

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Artificial Intelligence

Cite this

Idea divergent editor using analogy : The IDEA system. / Hayashi, Takashi; Hagiwara, Masafumi.

In: International Journal of Intelligent Systems, Vol. 18, No. 11, 11.2003, p. 1155-1172.

Research output: Contribution to journalArticle

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