Revealing Travel Patterns from Dockless Bike-sharing Data Based on Tensor Decomposition

Hao Tang · Sixiang Fei · Xiaoying Shi

7 citations0/0 files storedInternational Symposium on Visual Information Communication and Interaction (VINCI)

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Urban Transport and Accessibility Human Mobility and Location-Based Analysis Tensor decomposition and applications

Abstract

Dockless bike-sharing system has dramatically increased around the world since 2015, with the advantage of "free to leave" and "no fixed berth". Understanding the users' travel behavior is invaluable for policy makers and related companies. However, it is difficult to capture the spatio-temporal cycling patterns based on sparse bike-sharing data. In this paper, we analyze the dockless bike-sharing data using tensor decomposition method. A three-dimensional tensor is constructed first, and a tensor decomposition method is employed to detect the underlying travel patterns. Several visual components are designed to show the extracted patterns. The results demonstrate the effectiveness of our method.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 7 citations exist upstream.

References

2018Understanding the usage of dockless bike sharing in Singapore 2018A modeling framework for the dynamic management of free-floating bike-sharing systems 2019Unravel the landscape and pulses of cycling activities from a dockless bike-sharing system 2019A Deep Reinforcement Learning Framework for Rebalancing Dockless Bike Sharing Systems 2018A Two-Stage Destination Prediction Framework of Shared Bicycles Based on Geographical Position Recommendation 2018Origin and destination forecasting on dockless shared bicycle in a hybrid deep-learning algorithms

Cited by

2022Electric Fences for Dockless Bike-Sharing Systems: An Electric Fence-Planning Framework for a Dockless Bike-Sharing System Based on a Land Parcel Subdivision and Regional Coverage Maximization

Explore the map →

Papers that cite the same references — the relational fallback while embeddings are still backfilling.

Imported from OpenAlex (CC0) — nothing here is generated.