Research Mining using the Relationships among Authors, Topics and Papers

  • Authors:
  • Ryutaro Ichise;Setsu Fujita;Taichi Muraki;Hideaki Takeda

  • Affiliations:
  • National Institute of Informatics, Japan;TriAx Corporation;TriAx Corporation;National Institute of Informatics, Japan

  • Venue:
  • IV '07 Proceedings of the 11th International Conference Information Visualization
  • Year:
  • 2007

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Abstract

As information technology progress, we are able to obtain much information about the advanced research of others. As a result, researchers and research managers need to track the current research trends amid the information flood. In order to support these efforts to gather knowledge of current research, we propose a research trend mining method. The method utilizes an author-topic model for establishing the relationships between authors, topics, and papers by probabilities, and interactively visualizes the relationships using self-organizing maps. We implemented a research area mapping system and validated it with a case study. In addition, we conducted experiments to show the performance of our system. The experimental results indicate that this system can induce the appropriate relationships for finding research trends.