TraVis: An Interactive Visualization System for Mining Inbound Traveler Activities by Leveraging Mobile Ad Request Data
Authors: 
Pei-Xun Wang, Hsuan Chiu, Wen-Qian Chen, Che-Chia Chang, Yu-Hsuan Huang, Tzu-Hao Huang, Yuchun Lai, Chia-Hu ChangAuthors Info & Claims
Pei-Xun Wang, Hsuan Chiu, Wen-Qian Chen, Che-Chia Chang, Yu-Hsuan Huang, Tzu-Hao Huang, Yuchun Lai, Chia-Hu ChangAuthors Info & ClaimsPages 2881 - 2884
Abstract
The growth of inbound travel is fully coordinate with the successful urban development. Increasing the number of inbound travelers not only creates more jobs and economic opportunities but also drives the country toward prosperity. Thus, inbound traveler analysis through trajectory pattern mining, a subfield of urban computing, is regarded as a promising solution. This paper introduces large-scale mobile ad requests as an alternative data source of trajectory pattern mining in order to eliminate the limitations of conventional data sources, such as GPS data, cellular data, and IP address data. In addition, to expedite a comprehensive inbound traveler analysis, we build TraVis, a real-world system for efficiently exploring the inbound travelers' activities through the interactive visualization interface. By incorporating various modules, such as mobile users' home country and travel intent prediction, frequent trajectory pattern mining, and interactive visualization, TraVis proves the capability of profiling the travelers' behavior pattern. We use Japan inbound travelers in the case study to present the mining insights, and we also demonstrate the extensive system functionalities. Our system has been assisting Japan government agencies to formulate travel marketing strategies, including tourist experience enhancement and attractions marketing.
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Index Terms
- TraVis: An Interactive Visualization System for Mining Inbound Traveler Activities by Leveraging Mobile Ad Request Data
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Published In
November 2019
3373 pages
ISBN:9781450369763
DOI:10.1145/3357384
- General Chairs:
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- Dacheng Tao,
- Xueqi Cheng,
- Program Chairs:
- Peng Cui,
- Elke Rundensteiner,
- David Carmel,
- Qi He,
- Jeffrey Xu Yu
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Published: 03 November 2019
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CIKM '19: The 28th ACM International Conference on Information and Knowledge Management
November 3 - 7, 2019
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Overall Acceptance Rate 1,861 of 8,427 submissions, 22%
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