Automatic Topic Identification for Idea Summarization in Idea Visualization Programs

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概要

• 論文の詳細を見る

• Recent idea visualization programs still lack automatic idea summarization capabilities. This paper presents a knowledge-based method for automatically providing a short piece of English text about a topic to each idea group in idea charts. This automatic topic identification makes used Yet Another General Ontology (YAGO) and Wordnet as its knowledge bases. We propose a novel topic selection method and we compared its performance with three existing methods using two experimental datasets constructed using two idea visualization programs, i.e., the KJ Method (Kawakita Jiro Method) and mind-mapping programs. Our proposed topic identification method outperformed the baseline method in terms of both performance and consistency.

著者

• Kunifuji Susumu

  School Of Information Science Japan Advanced Institute Of Science And Technology Hokuriku

• VIRIYAYUDHAKORN Kobkrit

  School of Knowledge Science, Japan Advanced Institute of Science and Technology

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