ML Anthology

PARecommender: A Pattern-Based System for Route Recommendation

Feiyi Tang, Jia Zhu, Yang Cao, Sanli Ma, Yulong Chen, Jing He, Changqin Huang, Gansen Zhao, Yong Tang
IJCAI 2016 pp. 4272-4273
/ijcai/2016/tang2016ijcai-parecommender/

Abstract

Widely adoption of GPS-enabled devices generates massive trajectory data every minute. The trajectory data can generate meaningful traffic patterns. In this demo, we present a system called PARecommender, which predicts traffic conditions and provides route recommendation based on generated traffic patterns. We first introduce the technical details of PARecommender, and then show several real cases that how PARecommender works. PDF

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Cite

Text

Tang et al. "PARecommender: A Pattern-Based System for Route Recommendation." International Joint Conference on Artificial Intelligence, 2016.

Markdown

[Tang et al. "PARecommender: A Pattern-Based System for Route Recommendation." International Joint Conference on Artificial Intelligence, 2016.](https://mlanthology.org/ijcai/2016/tang2016ijcai-parecommender/)

BibTeX

@inproceedings{tang2016ijcai-parecommender,
  title     = {{PARecommender: A Pattern-Based System for Route Recommendation}},
  author    = {Tang, Feiyi and Zhu, Jia and Cao, Yang and Ma, Sanli and Chen, Yulong and He, Jing and Huang, Changqin and Zhao, Gansen and Tang, Yong},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2016},
  pages     = {4272-4273},
  url       = {https://mlanthology.org/ijcai/2016/tang2016ijcai-parecommender/}
}