Origin-Destination Extraction from Large-Scale Route Search Records for Tourism Trend Analysis

TL;DR

This paper introduces a method to convert large-scale expressway search logs into a 3D OD map, revealing tourism trends and aiding traffic and tourism planning through analysis of online search behaviors.

Contribution

It presents a novel approach for transforming massive route search data into a 3D OD map for tourism trend analysis, enabling efficient data compression and spatiotemporal analysis.

Findings

Strong correlation between search volume and peak tourism seasons

Visualization of tourist flow near popular attractions

Cyberspace behavioral data as a leading indicator of physical movement

Abstract

This paper presents a novel method for transforming large-scale historical expressway route search records into a three-dimensional (3D) Origin-Destination (OD) map, enabling data compression, efficient spatiotemporal sampling and statistical analysis. The study analyzed over 380 million expressway route search logs to investigate online search behavior related to tourist destinations. Several expressway interchanges (ICs) near popular attractions, such as those associated with spring flower viewing, autumn foliage and winter skiing, are examined and visualized. The results reveal strong correlations between search volume trends and the duration of peak tourism seasons. This approach leverages cyberspace behavioral data as a leading indicator of physical movement, providing a proactive tool for traffic management and tourism planning.