Workshop on Big Data Analytics for Enhancing Public Transport (BigTransport17)

November 8, 2017, Singapore

In Conjunction with ACM International Conference on Information and Knowledge Management (CIKM17), Singapore, November 7-10, 2017

Keynote Speaker

Dr. Xing Xie

Microsoft Research Asia

Introduction

Public transport is a critical component of smart city. In a dense urban city, public transport system is the preferred means to move people around. As the most sustainable and scalable solution, public transport now needs innovation to respond to new challenges brought by improving commuting experience.

These challenges include:

  1. Increased expectation of service quality, comfort and efficiency from commuters;
  2. Influx of new commuters working or visiting cities;
  3. Imbalanced supply and demand; and
  4. Last mile commuting gaps.

Meanwhile, public commuters today generate massive amount of data traces. These include: (i) sensor, image, and video data collected by the existing public transport infrastructure; (ii) train and bus trips recorded by electronic farecard systems; (iii) taxi bookings and taxi trips recorded by mobile apps; (iv) bicycle rental and biking trips recorded by bike sharing apps; and (v) social media posts on public transport events.

These rich data traces offer new opportunities for research in information retrieval, database, data mining and machine learning to enhance commuting experience enhancement, namely:

  • Identifying areas for public transport service improvement;
  • Discovering regular travel patterns of commuters;
  • Modelling and monitoring of commuting experience;
  • Personalizing public transport services to improve individual commuting experience; and
  • Engaging commuters in crowdsourcing resources to address unmet demand

Scope

The BigTransport workshop aims to bring researchers and practitioners across different Big Data and Public Transport research communities together in a unique forum to share the state-of-the-art technologies.

It welcomes researchers and practitioners to share the latest breakthroughs in analysing transport related data for improving commuting experience in public transport systems. These could include data science studies on commuter behavior, public transport data analytics applications and systems, large-scale behavioural experiments on public transport users, and simulation and visualization using massive public transport data. BigTransport will focus on application inspired novel findings, methods, systems and solutions which demonstrate the impact of big data analytics on public transport experience.

The workshop invites original contributions in the form of poster and demo papers covering but not limited to the following topics:

  • Public transport event detection
  • Ride/Taxi sharing system design
  • Commuting experience modelling and measurement
  • Emergency response systems
  • Walkability in urban cities
  • Real-time public transport system management
  • Social media analytics for commuter feedback
  • Last-mile commuting
  • Resilient public transport systems
  • Bike sharing
  • Recommender systems for commuters
  • Inclusive public transport
  • Intelligent commuter assistant
  • Commuter behavior sensing

Authors of all accepted submissions will be required to present their posters and demos at the workshop.

Workshop Organizers

Baihua Zheng, Singapore Management University

Chih-Chieh Hung, Tamkang University, Taiwan

Wang-Chien Lee, Penn State University, USA

Ee-Peng Lim, Singapore Management University

Paper Submission

Prospective authors are required to submit their papers electronically through EasyChair. Every poster/demo paper is limited to 4 pages in ACM proceedings format. All accepted papers will be shared with participants in an informal proceedings as well as on the workshop’s website.

Submission site: https://easychair.org/conferences/?conf=bigtransport17

The following are the important deadlines:

15 August: Paper submission

31 August: Paper acceptance notice

15 September: Camera-ready submission

Registration Fee Waiver for Poster/Demo Presenters

One presenter per poster/demo will be invited to join the workshop with registration fee waiver. If the presenter wishes to attend other parts of CIKM17 (workshops, tutorials, main conference tracks, etc.), the normal CIKM17 registration fees apply.

Programme Committee

Ling-Jyh Chen Academia Sinica

Shih-Fen Cheng Singapore Management University

Meng-Fen Chiang Living Analytic Research Centre, Singapore Management University

Chi-Yin Chow City University of Hong Kong

Yunjun Gao Zhejiang University

Hui-Huang Hsu Tamkang University

Haibo Hu Hong Kong Polytechnic University

Siyuan Liu Penn State University

Meng-Shiuan Pan Tamkang University

Chih-Ya Shen National Tsing Hua University

Hong-Han Shuai National Chiao Tung University

Yazhe Wang Living Analytic Research Centre, Singapore Management University

Hai Wang Singapore Management University

Fang-Jing Wu NEC Europe Labs

Jianliang Xu Hong Kong Baptist University

Dongxiang Zhang University of Electronic Science and Technology of China