Multi-Modal Transportation Recommendation with Unified Route Representation Learning

Summary: Unified route representation learning for multi-modal transport via time-dependent, multi-view GNNs with a coherence encoder. Hierarchical multi-task learning differentiates modes via coherence and feedback, beating eight baselines on two real datasets. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 12555
Venue: VLDB
Year: 2021
Pagerank: 4.6931334e-05
Overall Rank: 7,625 | 46.96%
DOI: 10.14778/3430915.3430924

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Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
10,233	Efficient GNN Training on Giant Graphs with Collective Batching and Scheduling	2026	VLDB	4.1945683e-05
11,253	Automatic Road Extraction with Multi-Source Data Revisited: Completeness, Smoothness and Discrimination	2023	VLDB	4.1945683e-05

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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank

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