The Community for Technology Leaders
2013 17th International Conference on Information Visualisation (2007)
Zurich, Switzerland
July 4, 2007 to July 6, 2007
ISSN: 1550-6037
ISBN: 0-7695-2900-3
pp: 425-430
Hideaki Takeda , National Institute of Informatics, Japan
Setsu Fujita , TriAx Corporation
Taichi Muraki , TriAx Corporation
Ryutaro Ichise , National Institute of Informatics, Japan
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.
Hideaki Takeda, Setsu Fujita, Taichi Muraki, Ryutaro Ichise, "Research Mining using the Relationships among Authors, Topics and Papers", 2013 17th International Conference on Information Visualisation, vol. 00, no. , pp. 425-430, 2007, doi:10.1109/IV.2007.95
95 ms
(Ver 3.3 (11022016))