Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport | Paper Citation Record

Observation 597be160-5dfc-42ec-989f-b9e1273de6f9 · outbound

This paper cites Complex network topology of transportation systems.Transport reviews, 33(6):658–685, 2013.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Complex network topology of transportation systems.Transport reviews, 33(6):658–685, 2013

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Observation 0e889712-07b4-46a8-9970-f7353bea9953 · outbound

This paper cites The network analysis of urban streets: a primal approach.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport The network analysis of urban streets: a primal approach

Reference 2

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Observation e9b5a74f-22cc-4f50-b345-e45c6ac31315 · outbound

This paper cites The network analysis of urban streets: a dual approach.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport The network analysis of urban streets: a dual approach

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Observation 1dc8c85f-2c6d-4392-a33f-f65d7bd94674 · outbound

This paper cites Network harness: Metropo- lis public transport.Physica A: Statistical Mechanics and its Applications, 380:585–591, 2007.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Network harness: Metropo- lis public transport.Physica A: Statistical Mechanics and its Applications, 380:585–591, 2007

Reference 4

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Observation f3ac4eab-01da-416c-b530-d20d75a8f921 · outbound

This paper cites Role of road network features in the evaluation of incident impacts on urban traffic mobility.Transportation research part B: methodological, 117:101–116, 2018.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Role of road network features in the evaluation of incident impacts on urban traffic mobility.Transportation research part B: methodological, 117:101–116, 2018

Reference 5

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Observation 51f2e282-224b-4060-8539-213933641b16 · outbound

This paper cites Statistical analysis of 22 public transport networks in poland.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Statistical analysis of 22 public transport networks in poland

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Observation b2945ce2-8b0b-47dc-92d3-82de4a93e91b · outbound

This paper cites Enforcing optimal routing through dynamic avoid- ance maps.Transportation Research Part B: Methodological, 149:118–137, 2021.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Enforcing optimal routing through dynamic avoid- ance maps.Transportation Research Part B: Methodological, 149:118–137, 2021

Reference 7

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Observation d30240cf-0b55-47f8-ab92-e57d3beebc98 · outbound

This paper cites On the spatial partitioning of urban transportation networks.Trans- portation Research Part B: Methodological, 46(10):1639–1656, 2012.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport On the spatial partitioning of urban transportation networks.Trans- portation Research Part B: Methodological, 46(10):1639–1656, 2012

Reference 8

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Observation a1710eaa-91ad-4a72-b148-6e0e649c3939 · outbound

This paper cites Identification of communities in urban mobility networks using multi-layer graphs of network traffic.Transportation Research Part C: Emerging Technologies, 89:254–267, 2018.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Identification of communities in urban mobility networks using multi-layer graphs of network traffic.Transportation Research Part C: Emerging Technologies, 89:254–267, 2018

Reference 9

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Observation f8c7e323-c12b-4b4e-970c-264afa8c36a7 · outbound

This paper cites A statistical method for estimating predictable differences between daily traffic flow profiles.Transportation Research Part B: Methodological, 95:196–213, 2017.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport A statistical method for estimating predictable differences between daily traffic flow profiles.Transportation Research Part B: Methodological, 95:196–213, 2017

Reference 10

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Observation 4c2f4e85-5220-477a-8e69-5cc8e207f925 · outbound

This paper cites Valuing travel time variability: Characteristics of the travel time distribution on an urban road.Transportation Research Part C: Emerging Technologies, 24:83–101, 2012.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Valuing travel time variability: Characteristics of the travel time distribution on an urban road.Transportation Research Part C: Emerging Technologies, 24:83–101, 2012

Reference 11

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Observation 7d860566-bd93-4e7c-9a75-d4dd5c2c9ac6 · outbound

This paper cites Clustering of heterogeneous networks with directional flows based on “snake” similarities.Transportation Research Part B: Methodological, 91:250– 269, 2016.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Clustering of heterogeneous networks with directional flows based on “snake” similarities.Transportation Research Part B: Methodological, 91:250– 269, 2016

Reference 12

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Observation 23a06e2b-2ba9-4f41-a550-a3574247ed16 · outbound

This paper cites Current trends in road traffic network division for distributed or parallel road traffic simulation.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Current trends in road traffic network division for distributed or parallel road traffic simulation

Reference 13

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Observation 93be8c2a-1896-481d-9e80-038c110778bd · outbound

This paper cites A decomposition approach to the static traffic assignment problem.Transportation Research Part B: Methodological, 105:270–296, 2017.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport A decomposition approach to the static traffic assignment problem.Transportation Research Part B: Methodological, 105:270–296, 2017

Reference 14

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Observation fd127865-8168-4ea4-8c3c-ed3c0fe9eaf6 · outbound

This paper cites A partitioning strategy for nonuniform problems on multiproces- sors.IEEE Transactions on Computers, 100(5):570–580, 1987.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport A partitioning strategy for nonuniform problems on multiproces- sors.IEEE Transactions on Computers, 100(5):570–580, 1987

Reference 15

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Observation a83febe7-0744-4aa9-a1c9-ced7ace24703 · outbound

This paper cites Spartsim: A space partitioning guided by road network for distributed traffic simulations.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Spartsim: A space partitioning guided by road network for distributed traffic simulations

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Observation eccbc88d-b2c2-4dce-9664-829cc1383844 · outbound

This paper cites an unresolved cited work.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Unresolved cited work

Reference 17

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Observation d7807a47-6c89-4378-b831-6d17bfba6913 · outbound

This paper cites Vu, and Christopher Leckie.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Vu, and Christopher Leckie

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Observation 29f470ce-8923-47a4-af0b-2f6787db271d · outbound

This paper cites Road network partitioning method based on canopyk-means clustering algorithm.Archives of Transport, 54(2):95–106, 2020.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Road network partitioning method based on canopyk-means clustering algorithm.Archives of Transport, 54(2):95–106, 2020

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Observation 604ffea5-d6f6-46a6-b713-cfeb85bd3167 · outbound

This paper cites Dynamics of heterogeneity in urban net- works: aggregated traffic modeling and hierarchical control.Transportation Research Part B: Method- ological, 74:1–19, 2015.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Dynamics of heterogeneity in urban net- works: aggregated traffic modeling and hierarchical control.Transportation Research Part B: Method- ological, 74:1–19, 2015

Reference 20

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Observation 5e9c2cf1-d20a-4eeb-86ce-72e1b973503a · outbound

This paper cites Mode differentiation in par- titioning of mixed bi-modal urban networks.Transportmetrica B: Transport Dynamics, 11(1):463–485, 2023.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Mode differentiation in par- titioning of mixed bi-modal urban networks.Transportmetrica B: Transport Dynamics, 11(1):463–485, 2023

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Observation b072a991-bbbc-466e-9f19-28d7fe638d9f · outbound

This paper cites Exploring dynamic urban mobility patterns from traffic flow data using community detection.Annals of GIS, 30(4):435–454, 2024.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Exploring dynamic urban mobility patterns from traffic flow data using community detection.Annals of GIS, 30(4):435–454, 2024

Reference 22

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Observation 4ce6e05d-6bf4-4063-995f-e336f363486b · outbound

This paper cites Comparing community detection algorithms in transport networks via points of interest.IEEE Access, 6:29729–29738, 2018.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Comparing community detection algorithms in transport networks via points of interest.IEEE Access, 6:29729–29738, 2018

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Observation eaa073b6-511d-4be3-bc10-6e38b338f78f · outbound

This paper cites Analyzing a multilayer comprehen- sive passenger transport network through overlapping community detection.Transportation Research Record, 2678(11):1517–1532, 2024.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Analyzing a multilayer comprehen- sive passenger transport network through overlapping community detection.Transportation Research Record, 2678(11):1517–1532, 2024

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Observation 3146891e-943c-4fb5-8512-110b1b1bd015 · outbound

This paper cites Designing bike networks using the concept of network clusters.Applied network science, 3(1):12, 2018.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Designing bike networks using the concept of network clusters.Applied network science, 3(1):12, 2018

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Observation 1456fa7a-8760-4a94-b0cb-acd1962a7473 · outbound

This paper cites The structure of spatial networks and communities in bicycle sharing systems.PloS One, 8(9):e74685, 2013.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport The structure of spatial networks and communities in bicycle sharing systems.PloS One, 8(9):e74685, 2013

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Observation fe948a09-1c29-4e5d-9228-f00c878aa138 · outbound

This paper cites Exploring the spatiotemporal patterns of shared bicycle usage: a case study of metrobike in austin, texas.Computational Urban Science, 5(1):52, 2025.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Exploring the spatiotemporal patterns of shared bicycle usage: a case study of metrobike in austin, texas.Computational Urban Science, 5(1):52, 2025

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Observation 75cc9c17-7d0e-4770-8077-cdd8567eab35 · outbound

This paper cites Study on community detection method for morning and evening peak shared bicycle trips in urban areas: A case study of six districts in beijing.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Study on community detection method for morning and evening peak shared bicycle trips in urban areas: A case study of six districts in beijing

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Observation 2fb7c8a7-dc9a-458f-b59e-d83b49e6c5eb · outbound

This paper cites A survey of kernel and spectral methods for clustering.Pattern recognition, 41(1):176–190, 2008.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport A survey of kernel and spectral methods for clustering.Pattern recognition, 41(1):176–190, 2008

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Observation b2045935-5d36-4b2b-81cd-18ff44d7db51 · outbound

This paper cites An efficient heuristic procedure for partitioning graphs.The Bell system technical journal, 49(2):291–307, 1970.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport An efficient heuristic procedure for partitioning graphs.The Bell system technical journal, 49(2):291–307, 1970

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Observation aa30b859-ba38-4565-9bd3-4e674ce92a6e · outbound

This paper cites Metis: A software package for partitioning unstructured graphs, partitioning meshes, and computing fill-reducing orderings of sparse matrices.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Metis: A software package for partitioning unstructured graphs, partitioning meshes, and computing fill-reducing orderings of sparse matrices

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Observation cf8d3956-f286-445e-aa0b-f14b60c620b1 · outbound

This paper cites Partitioning of urban transportation networks utilizing real-world traffic parameters for distributed simulation in sumo.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Partitioning of urban transportation networks utilizing real-world traffic parameters for distributed simulation in sumo

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Observation 0bcebf3b-a00a-436b-926d-e348797a1d90 · outbound

This paper cites A graph partitioning algorithm for parallel agent-based road traffic simulation.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport A graph partitioning algorithm for parallel agent-based road traffic simulation

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Observation 2cfe6595-84c6-49ff-915e-3f23a68806ec · outbound

This paper cites Normalized cuts and image segmentation.IEEE Transactions on pattern analysis and machine intelligence, 22(8):888–905, 2000.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Normalized cuts and image segmentation.IEEE Transactions on pattern analysis and machine intelligence, 22(8):888–905, 2000

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Observation 7ce713b6-8517-4337-8e53-9cc1dc917233 · outbound

This paper cites Investigating transport network vulnerability by capacity weighted spectral analysis.Transportation Research Part B: Methodological, 99:251–266, 2017.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Investigating transport network vulnerability by capacity weighted spectral analysis.Transportation Research Part B: Methodological, 99:251–266, 2017

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Observation 4449e83e-6c83-40ef-8ef4-ff11f717fd38 · outbound

This paper cites Evolutionary spectral clustering by incorporating temporal smoothness.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Evolutionary spectral clustering by incorporating temporal smoothness

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Observation 7ec7753a-4c39-4c26-b6d1-8d933f2885f3 · outbound

This paper cites Partitioning of transporta- tion networks by efficient evolutionary clustering and density peaks.Algorithms, 15(3):76, 2022.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Partitioning of transporta- tion networks by efficient evolutionary clustering and density peaks.Algorithms, 15(3):76, 2022

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Observation 06c1c7d0-35b0-471c-9b0e-ce2003615b77 · outbound

This paper cites Symnmf: nonnegative low-rank approximation of a simi- larity matrix for graph clustering.Journal of Global Optimization, 62(3):545–574, 2015.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Symnmf: nonnegative low-rank approximation of a simi- larity matrix for graph clustering.Journal of Global Optimization, 62(3):545–574, 2015

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Observation 71ff4389-bd36-4335-9d3e-7e38a1dfa8f4 · outbound

This paper cites A new combinatorial characteristic parameter for clustering-based traffic network partitioning.IEEE Access, 7:40175–40182, 2019.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport A new combinatorial characteristic parameter for clustering-based traffic network partitioning.IEEE Access, 7:40175–40182, 2019

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Observation 8f32b259-12ab-486e-adf1-b6535aa56aec · outbound

This paper cites Finding community structure in very large networks.Physical Review E—Statistical, Nonlinear, and Soft Matter Physics, 70(6):066111, 2004.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Finding community structure in very large networks.Physical Review E—Statistical, Nonlinear, and Soft Matter Physics, 70(6):066111, 2004

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Observation a06cefdb-6303-425e-b5f4-17b056d45c1a · outbound

This paper cites Fast unfolding of communities in large networks.Journal of statistical mechanics: theory and experiment, 2008(10):P10008, 2008.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Fast unfolding of communities in large networks.Journal of statistical mechanics: theory and experiment, 2008(10):P10008, 2008

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Observation c318a9d1-da5b-4b36-a6c8-a969d5c2e541 · outbound

This paper cites Shared bicycles in a city: A signal processing and data analysis perspective.Advances in Complex Sys- tems, 14(03):415–438, 2011.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Shared bicycles in a city: A signal processing and data analysis perspective.Advances in Complex Sys- tems, 14(03):415–438, 2011

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Observation 1355f58b-1e3c-4b19-846e-9cb419529ed0 · outbound

This paper cites Multi-scale analysis of the european airspace using network community de- tection.PloS One, 9(5):e94414, 2014.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Multi-scale analysis of the european airspace using network community de- tection.PloS One, 9(5):e94414, 2014

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Observation aba562e3-3147-404d-a98f-3f309d0ca521 · outbound

This paper cites General optimization tech- nique for high-quality community detection in complex networks.Physical Review E, 90(1):012811, 2014.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport General optimization tech- nique for high-quality community detection in complex networks.Physical Review E, 90(1):012811, 2014

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Observation 7100862a-710f-4898-b2e6-e25e9d76e739 · outbound

This paper cites Identifying spatial structure of travel modes through community detection method.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Identifying spatial structure of travel modes through community detection method

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Observation 062d332b-92cd-4b0f-a6b3-8af8e9d59b32 · outbound

This paper cites From louvain to leiden: guaranteeing well- connected communities.Scientific reports, 9(1):1–12, 2019.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport From louvain to leiden: guaranteeing well- connected communities.Scientific reports, 9(1):1–12, 2019

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Resolution: unresolved; no resolver link, observed 2026-07-31T12:59:32.973159Z

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Observation 6a9b15dc-71c5-4cad-8a03-47cfefa77f7d · outbound

This paper cites an unresolved cited work.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Unresolved cited work

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Observation 139c22ad-3022-4ede-a1d8-6f1682d19138 · outbound

This paper cites Maps of random walks on complex networks reveal community structure.Proceedings of the national academy of sciences, 105(4):1118–1123, 2008.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Maps of random walks on complex networks reveal community structure.Proceedings of the national academy of sciences, 105(4):1118–1123, 2008

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Observation 224f7d31-9c4c-4ad0-ad75-47234b90ec0b · outbound

This paper cites Computing communities in large networks using random walks.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Computing communities in large networks using random walks

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Observation c0658b95-430c-46c7-b574-8833938ddc79 · outbound

This paper cites How good is recursive bisection?SIAM Journal on Scientific Computing, 18(5):1436–1445, 1997.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport How good is recursive bisection?SIAM Journal on Scientific Computing, 18(5):1436–1445, 1997

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Observation 0355638d-5455-448e-84ec-8fe94d5c6d0a · outbound

This paper cites An improved road network partition algorithm for parallel micro- scopic traffic simulation.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport An improved road network partition algorithm for parallel micro- scopic traffic simulation

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Observation 20296688-0c8c-4826-bdde-d9f5be7cfdf9 · outbound

This paper cites Algorithm as 136: Ak-means clustering algorithm.Journal of the royal statistical society.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Algorithm as 136: Ak-means clustering algorithm.Journal of the royal statistical society

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Observation e94c1ad1-8463-4938-b24b-935630de65f9 · outbound

This paper cites Generalized net- work voronoi diagrams: Concepts, computational methods, and applications.International Journal of Geographical Information Science, 22(9):965–994, 2008.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Generalized net- work voronoi diagrams: Concepts, computational methods, and applications.International Journal of Geographical Information Science, 22(9):965–994, 2008

Reference 53

Resolution: unresolved; no resolver link, observed 2026-07-31T12:59:33.002752Z

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Observation b2379e4c-32bd-4e11-998b-c1c072463ec1 · outbound

This paper cites A spatio-temporal co-clustering framework for discovering mobility patterns: A study of manhattan taxi data.IEEE Access, 9:34338– 34351, 2021.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport A spatio-temporal co-clustering framework for discovering mobility patterns: A study of manhattan taxi data.IEEE Access, 9:34338– 34351, 2021

Reference 54

Resolution: unresolved; no resolver link, observed 2026-07-31T12:59:33.006793Z

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Observation 0ced219b-2a7c-46fd-90cb-f471ba40d06d · outbound

This paper cites Victs: A novel network partition algorithm for scal- able agent-based modeling of mass evacuation.Computers, Environment and Urban Systems, 80:101452, 2020.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Victs: A novel network partition algorithm for scal- able agent-based modeling of mass evacuation.Computers, Environment and Urban Systems, 80:101452, 2020

Reference 55

Resolution: unresolved; no resolver link, observed 2026-07-31T12:59:33.010659Z

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Observation 81177096-504d-4858-9c73-f0b3c1889a56 · outbound

This paper cites Survey of spectral clustering based on graph theory.Pattern Recognition, 151:110366, 2024.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Survey of spectral clustering based on graph theory.Pattern Recognition, 151:110366, 2024

Reference 56

Resolution: unresolved; no resolver link, observed 2026-07-31T12:59:33.014714Z

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Observation 90a8949d-d8be-481b-b1b9-19ae544b57f5 · outbound

This paper cites Finding and evaluating community structure in networks.Phys- ical review E, 69(2):026113, 2004.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Finding and evaluating community structure in networks.Phys- ical review E, 69(2):026113, 2004

Reference 57

Resolution: unresolved; no resolver link, observed 2026-07-31T12:59:33.018709Z

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Observation 6fb1fcbc-521e-46cf-b426-7954342302b8 · outbound

This paper cites Finding overlapping communities in multilayer networks.PloS One, 13(4):e0188747, 2018.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Finding overlapping communities in multilayer networks.PloS One, 13(4):e0188747, 2018

Reference 58

Resolution: unresolved; no resolver link, observed 2026-07-31T12:59:33.022597Z

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Observation e712f854-136d-4fae-9019-af3cb93c15d6 · outbound

This paper cites Least squares quantization in pcm.IEEE transactions on information theory, 28(2):129–137, 1982.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Least squares quantization in pcm.IEEE transactions on information theory, 28(2):129–137, 1982

Reference 59

Resolution: unresolved; no resolver link, observed 2026-07-31T12:59:33.026832Z

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Observation 4a43be95-963f-4e7a-8815-f29f05b0789e · outbound

This paper cites Dynamic time warping algorithm review.Information and Computer Science Department University of Hawaii at Manoa Honolulu, USA, 855(1-23):40, 2008.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Dynamic time warping algorithm review.Information and Computer Science Department University of Hawaii at Manoa Honolulu, USA, 855(1-23):40, 2008

Reference 60

Resolution: unresolved; no resolver link, observed 2026-07-31T12:59:33.031156Z

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Observation 18bfc9d8-8430-4acb-9ef2-57362d9d8a5b · outbound

This paper cites A modified hausdorff distance for object matching.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport A modified hausdorff distance for object matching

Reference 61

Resolution: unresolved; no resolver link, observed 2026-07-31T12:59:33.035213Z

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Observation 91e74228-47cc-4da7-84ae-55507c855b37 · outbound

This paper cites Community detection in node-attributed social networks: a survey.Computer Science Review, 37:100286, 2020.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Community detection in node-attributed social networks: a survey.Computer Science Review, 37:100286, 2020

Reference 62

Resolution: unresolved; no resolver link, observed 2026-07-31T12:59:33.039117Z

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Observation 1f30f464-af59-469c-a75a-78deb16df172 · outbound

This paper cites Gromov-wasserstein averaging of kernel and distance matrices.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Gromov-wasserstein averaging of kernel and distance matrices

Reference 63

Resolution: unresolved; no resolver link, observed 2026-07-31T12:59:33.042947Z

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Observation 6a665d4a-db3f-4c10-afb6-1c75c99edb35 · outbound

This paper cites Gromov–wasserstein distances and the metric approach to object matching.Founda- tions of computational mathematics, 11(4):417–487, 2011.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Gromov–wasserstein distances and the metric approach to object matching.Founda- tions of computational mathematics, 11(4):417–487, 2011

Reference 64

Resolution: unresolved; no resolver link, observed 2026-07-31T12:59:33.047067Z

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Observation 8077ee22-fcdc-44d3-ad25-968634ce9cb2 · outbound

This paper cites Semi-relaxed Gromov-Wasserstein divergence with applications on graphs.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Semi-relaxed Gromov-Wasserstein divergence with applications on graphs

Reference 65

Resolution: unresolved; no resolver link, observed 2026-07-31T12:59:33.051220Z

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Observation 88c2b0d3-1b7a-44c7-9655-a6029f804951 · outbound

This paper cites Optimal transport for structured data with application on graphs.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Optimal transport for structured data with application on graphs

Reference 66

Resolution: unresolved; no resolver link, observed 2026-07-31T12:59:33.055497Z

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Observation 88f504d6-5214-40ac-877a-9957c2c0135a · outbound

This paper cites Optimal Transport-Based Clustering of Attributed Graphs with an Application to Road Traffic Data.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Optimal Transport-Based Clustering of Attributed Graphs with an Application to Road Traffic Data

Reference 67

Resolution: unresolved; no resolver link, observed 2026-07-31T12:59:33.059125Z

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Observation 52320953-e3d3-4d39-8874-dce3f9de70d4 · outbound

This paper cites Pot: Python optimal transport.Journal of Machine Learning Research, 22(78):1–8, 2021.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Pot: Python optimal transport.Journal of Machine Learning Research, 22(78):1–8, 2021

Reference 68

Resolution: unresolved; no resolver link, observed 2026-07-31T12:59:33.063448Z

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Observation 08f3fc87-c74e-4c28-9e68-1c88ca3eb752 · outbound

This paper cites Cross- comparison of network clustering methods: Potential macroscopic fundamental diagram (mfd)-based applications.Transportation Research Record, 2679(12):514–532, 2025.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Cross- comparison of network clustering methods: Potential macroscopic fundamental diagram (mfd)-based applications.Transportation Research Record, 2679(12):514–532, 2025

Reference 69

Resolution: unresolved; no resolver link, observed 2026-07-31T12:59:33.067531Z

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Observation 4fea4445-7bcf-4f5c-9687-bc2eb54f8589 · outbound

This paper cites Modularity and community structure in networks.Proceedings of the national academy of sciences, 103(23):8577–8582, 2006.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Modularity and community structure in networks.Proceedings of the national academy of sciences, 103(23):8577–8582, 2006

Reference 70

Resolution: unresolved; no resolver link, observed 2026-07-31T12:59:33.071464Z

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Observation 4c39e842-f13d-4306-89e4-c2522e28024a · outbound

This paper cites Lessons from thirteen years of the london cycle hire scheme: A review of evidence.Multimodal Transportation, 3(3):100156, 2024.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Lessons from thirteen years of the london cycle hire scheme: A review of evidence.Multimodal Transportation, 3(3):100156, 2024

Reference 71

Resolution: unresolved; no resolver link, observed 2026-07-31T12:59:33.075223Z

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Observation c2a5ce6b-b2bc-4799-884f-c1fab243b479 · outbound

This paper cites Community structures, interactions and dynamics in london’s bicycle sharing network.

Integrating Structure and Attributes for Transportation Network Partitioning via Optimal Transport Community structures, interactions and dynamics in london’s bicycle sharing network

Reference 72

Resolution: unresolved; no resolver link, observed 2026-07-31T12:59:33.079112Z

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