Visualization System for Exploratory Analysis of Time-series Data: Alignment Method between Articles and Time-series Data

Abstract

The goal of our study is to support a user's analysis of time-series data in an exploratory manner. Such exploratory analysis requires repeated access to various types of information related to the user's interests such as texts and numerical data. To support such the user's analysis, we have proposed a system that visualizes temporal changes in time-series data and presents the causes of those changes with the data. In this paper, we improve the system by adding an alignment function between news articles and time-series data. By using this function, the user can find articles that relates to the time-series data easily.