The Third Workshop on Data-driven Intelligent Transportation

Hua Wei; Guni Sheron; Cathy Wu; Sanjay Chawla; Zhenhui Li

doi:10.1145/3511808.3557496

The Third Workshop on Data-driven Intelligent Transportation

Hua Wei
, Guni Sheron
, Cathy Wu
, Sanjay Chawla
, Zhenhui Li

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

Traffic is the pulse of the city. Transportation systems can involve humans, vehicles, shipments, information technology, and the physical infrastructure, all interacting in complex ways. Intelligent transportation enables the city to function in a more efficient and effective way. A wide range of city data become increasingly available, such as taxi trips, surveillance camera data, human mobility data from mobile phones or location-based services, events from social media, car accident reports, bike-sharing information, Points-Of-Interest, traffic sensors, public transportation data, and many more. This abundance of data poses a grand challenge to the CIKM research community: How to utilize such data toward city intelligence, across various transportation tasks? The 3rd workshop of "Data-driven Intelligent Transportation"welcomes articles and presentations in the areas of transportation systems, data mining, and artificial intelligence, conveying new advances and developments in theory, modeling, simulation, testing, case studies, as well as large-scale deployment.

Original language	English
Title of host publication	CIKM 2022 - Proceedings of the 31st ACM International Conference on Information and Knowledge Management
Publisher	Association for Computing Machinery
Pages	5177-5178
Number of pages	2
ISBN (Electronic)	9781450392365
DOIs	https://doi.org/10.1145/3511808.3557496
State	Published - 17 Oct 2022
Externally published	Yes
Event	31st ACM International Conference on Information and Knowledge Management, CIKM 2022 - Atlanta, United States Duration: 17 Oct 2022 → 21 Oct 2022

Publication series

Name	International Conference on Information and Knowledge Management, Proceedings
ISSN (Print)	2155-0751

Conference

Conference	31st ACM International Conference on Information and Knowledge Management, CIKM 2022
Country/Territory	United States
City	Atlanta
Period	17/10/22 → 21/10/22

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being
SDG 11 Sustainable Cities and Communities

Keywords

spatio-temporal data mining
transportation
urban computing

ASJC Scopus subject areas

General Business, Management and Accounting
General Decision Sciences

Access to Document

10.1145/3511808.3557496

Cite this

Wei, H., Sheron, G., Wu, C., Chawla, S., & Li, Z. (2022). The Third Workshop on Data-driven Intelligent Transportation. In CIKM 2022 - Proceedings of the 31st ACM International Conference on Information and Knowledge Management (pp. 5177-5178). (International Conference on Information and Knowledge Management, Proceedings). Association for Computing Machinery. https://doi.org/10.1145/3511808.3557496

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title = "The Third Workshop on Data-driven Intelligent Transportation",

abstract = "Traffic is the pulse of the city. Transportation systems can involve humans, vehicles, shipments, information technology, and the physical infrastructure, all interacting in complex ways. Intelligent transportation enables the city to function in a more efficient and effective way. A wide range of city data become increasingly available, such as taxi trips, surveillance camera data, human mobility data from mobile phones or location-based services, events from social media, car accident reports, bike-sharing information, Points-Of-Interest, traffic sensors, public transportation data, and many more. This abundance of data poses a grand challenge to the CIKM research community: How to utilize such data toward city intelligence, across various transportation tasks? The 3rd workshop of {"}Data-driven Intelligent Transportation{"}welcomes articles and presentations in the areas of transportation systems, data mining, and artificial intelligence, conveying new advances and developments in theory, modeling, simulation, testing, case studies, as well as large-scale deployment.",

keywords = "spatio-temporal data mining, transportation, urban computing",

author = "Hua Wei and Guni Sheron and Cathy Wu and Sanjay Chawla and Zhenhui Li",

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doi = "10.1145/3511808.3557496",

language = "English",

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Wei, H, Sheron, G, Wu, C, Chawla, S & Li, Z 2022, The Third Workshop on Data-driven Intelligent Transportation. in CIKM 2022 - Proceedings of the 31st ACM International Conference on Information and Knowledge Management. International Conference on Information and Knowledge Management, Proceedings, Association for Computing Machinery, pp. 5177-5178, 31st ACM International Conference on Information and Knowledge Management, CIKM 2022, Atlanta, United States, 17/10/22. https://doi.org/10.1145/3511808.3557496

The Third Workshop on Data-driven Intelligent Transportation. / Wei, Hua; Sheron, Guni; Wu, Cathy et al.
CIKM 2022 - Proceedings of the 31st ACM International Conference on Information and Knowledge Management. Association for Computing Machinery, 2022. p. 5177-5178 (International Conference on Information and Knowledge Management, Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - The Third Workshop on Data-driven Intelligent Transportation

AU - Wei, Hua

AU - Sheron, Guni

AU - Wu, Cathy

AU - Chawla, Sanjay

AU - Li, Zhenhui

PY - 2022/10/17

Y1 - 2022/10/17

N2 - Traffic is the pulse of the city. Transportation systems can involve humans, vehicles, shipments, information technology, and the physical infrastructure, all interacting in complex ways. Intelligent transportation enables the city to function in a more efficient and effective way. A wide range of city data become increasingly available, such as taxi trips, surveillance camera data, human mobility data from mobile phones or location-based services, events from social media, car accident reports, bike-sharing information, Points-Of-Interest, traffic sensors, public transportation data, and many more. This abundance of data poses a grand challenge to the CIKM research community: How to utilize such data toward city intelligence, across various transportation tasks? The 3rd workshop of "Data-driven Intelligent Transportation"welcomes articles and presentations in the areas of transportation systems, data mining, and artificial intelligence, conveying new advances and developments in theory, modeling, simulation, testing, case studies, as well as large-scale deployment.

AB - Traffic is the pulse of the city. Transportation systems can involve humans, vehicles, shipments, information technology, and the physical infrastructure, all interacting in complex ways. Intelligent transportation enables the city to function in a more efficient and effective way. A wide range of city data become increasingly available, such as taxi trips, surveillance camera data, human mobility data from mobile phones or location-based services, events from social media, car accident reports, bike-sharing information, Points-Of-Interest, traffic sensors, public transportation data, and many more. This abundance of data poses a grand challenge to the CIKM research community: How to utilize such data toward city intelligence, across various transportation tasks? The 3rd workshop of "Data-driven Intelligent Transportation"welcomes articles and presentations in the areas of transportation systems, data mining, and artificial intelligence, conveying new advances and developments in theory, modeling, simulation, testing, case studies, as well as large-scale deployment.

KW - spatio-temporal data mining

KW - transportation

KW - urban computing

UR - https://www.scopus.com/pages/publications/85140885265

U2 - 10.1145/3511808.3557496

DO - 10.1145/3511808.3557496

M3 - Conference contribution

AN - SCOPUS:85140885265

T3 - International Conference on Information and Knowledge Management, Proceedings

SP - 5177

EP - 5178

BT - CIKM 2022 - Proceedings of the 31st ACM International Conference on Information and Knowledge Management

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ER -

Wei H, Sheron G, Wu C, Chawla S, Li Z. The Third Workshop on Data-driven Intelligent Transportation. In CIKM 2022 - Proceedings of the 31st ACM International Conference on Information and Knowledge Management. Association for Computing Machinery. 2022. p. 5177-5178. (International Conference on Information and Knowledge Management, Proceedings). doi: 10.1145/3511808.3557496

The Third Workshop on Data-driven Intelligent Transportation

Abstract

Publication series

Conference

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this