抄録
This paper proposes a data annotation system using the automatic tagging approach. Although annotations of data are useful for deep analysis and mining of it, the cost of providing them becomes huge in most of the cases. In order to solve this problem, we develop a semi-automatic method that consists of two stages. In the first stage, it searches the Web space for relating information, and discovers candidates of effective annotations. The second stage uses knowledge of a human user. The candidates are investigated and refined by the user, and then they become annotations. We in this paper focus on time-series data, and show effectiveness of a GUI tool that supports the above process.
