MCC-Vis: Visual Analysis for City Regional Co-occurrence Pattern Based on Traffic Trajectory Data-Reference-Cited by-同舟云学术

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MCC-Vis: Visual Analysis for City Regional Co-occurrence Pattern Based on Traffic Trajectory Data

Published:2022-08-19 Issue: Volume: Page:
ISSN:
Container-title:2022 5th International Conference on Pattern Recognition and Artificial Intelligence (PRAI)
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Author:

Wang Zhong¹,Han Yongguo¹,Wang Guijuan²,Zhao Weixin¹,Wang Jiansong¹,Wu Yadong³

Affiliation:

1. Southwest University of Science and Technology,School of Computer and Technology,Mianyang,China

2. Southwest University of Science and Technology,Information and Technology School,Computer Science and Technology School,Mianyang,China

3. Sichuan University of Science and Engineering,School of Computer and Technology,Zigong,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9904023/9904007/09904131.pdf?arnumber=9904131

Reference20 articles.

1. POI2Vec: Geographical Latent Representation for Predicting Future Visitors

2. Road2Vec: Measuring Traffic Interactions in Urban Road System from Massive Travel Routes

3. Location2vec: A Situation-Aware Representation for Visual Exploration of Urban Locations

4. FGVis: visual analytics of human mobility patterns and urban areas based on F-GloVe

5. NodeSense2Vec: Spatiotemporal Context-Aware Network Embedding for Heterogeneous Urban Mobility Data

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