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CIKM 2019 Workshop on Artificial Intelligence in Transportation (AI in transportation)

Published: 03 November 2019 Publication History

Abstract

Data-enabled smart transportation has attracted a surge of interest from machine learning and data mining researchers nowadays due to the bloom of online ride-hailing industry and rapid development of autonomous driving. Large-scale high quality route data and trading data (spatiotemporal data) have been generated every day, which makes AI an urgent need and preferred solution for the decision making in intelligent transportation systems. While a large of amount of work have been dedicated to traditional transportation problems, they are far from satisfactory for the rising need. We propose a half-day workshop at CIKM 2019 for the professionals, researchers, and practitioners who are interested in mining and understanding big and heterogeneous data generated in transportation, and AI applications to improve the transportation system. We plan to have several invited talks from both academia and industry. This workshop would be organized by Shanghai Jiao Tong University, Didi Chuxing and Pennsylvania State University.

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  1. CIKM 2019 Workshop on Artificial Intelligence in Transportation (AI in transportation)

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      cover image ACM Conferences
      CIKM '19: Proceedings of the 28th ACM International Conference on Information and Knowledge Management
      November 2019
      3373 pages
      ISBN:9781450369763
      DOI:10.1145/3357384
      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 03 November 2019

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      Author Tags

      1. ai in transportation
      2. machine learning
      3. spatio-temperal data mining
      4. urban computing

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      CIKM '19
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      Acceptance Rates

      CIKM '19 Paper Acceptance Rate 202 of 1,031 submissions, 20%;
      Overall Acceptance Rate 1,861 of 8,427 submissions, 22%

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      CIKM '25

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