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Debunking the Myths of Influence Maximization: An In-Depth Benchmarking Study.

, , and . SIGMOD Conference, page 651-666. ACM, (2017)

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A weight-based map matching algorithm using minimum input variables for urban road networks., , , and . COMSNETS, page 437-442. IEEE, (2017)Trajectory Analytics: Indexing, Mining, and Applications to Network Optimization., , and . COMAD, page 11. Computer Society of India, (2013)LIMIP: Lifelong Learning to Solve Mixed Integer Programs., and . AAAI, page 9047-9054. AAAI Press, (2023)MANTRA: A Scalable Approach to Mining Temporally Anomalous Sub-trajectories., , and . KDD, page 1415-1424. ACM, (2016)Inferring Uncertain Trajectories from Partial Observations., , and . CoRR, (2016)Efficiently Answering Regular Simple Path Queries on Large Labeled Networks., , , , and . SIGMOD Conference, page 1463-1480. ACM, (2019)GraphSig: A Scalable Approach to Mining Significant Subgraphs in Large Graph Databases., and . ICDE, page 844-855. IEEE Computer Society, (2009)NetClus: A Scalable Framework for Locating Top-K Sites for Placement of Trajectory-Aware Services., , , , , and . ICDE, page 87-90. IEEE Computer Society, (2017)Influence Maximization Revisited: The State of the Art and the Gaps that Remain., , and . EDBT, page 440-443. OpenProceedings.org, (2019)TAGMol: Target-Aware Gradient-guided Molecule Generation., , , , , , , and . CoRR, (2024)