Source-for-Transportation

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Source-for-Transportation

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Relation Source for Transportation

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# Source-for-Transportation
Relation Source for Transportation
### Paper List
1. [GNN4Traffic->Paper-List-for-Transportation](https://github.com/jwwthu/GNN4Traffic)
2. [Bigscity-LibCity-PaperList->Paper-List-for-Transportation](https://github.com/LibCity/Bigscity-LibCity-PaperList)
3. [DL4Traffic](https://github.com/jwwthu/DL4Traffic)
4. [HIN source](http://www.shichuan.org/HIN_topic.html)

### Code
1. [多模态交通推荐-百度baseline](https://github.com/xuaikun/Paddle_baseline_KDD2019)
2. [多模态交通推荐](https://github.com/ywc1026/KDD-CUP-2019)
3. [多模态交通推荐-MTRecS-DLT](https://github.com/xuaikun/MTRecS-DLT)
4. [交通方面的代码](https://github.com/aptx1231/Traffic-Prediction-Open-Code-Summary)

### Dataset
1. [Bus Data](http://motor.ece.iit.edu/Data/)
2. [TransportationNetworks](https://github.com/bstabler/TransportationNetworks)
3. [新加坡交通数据集](https://data.gov.sg/dataset?organization=land-transport-authority&groups=transport)
4. [斯坦福交通数据集](https://snap.stanford.edu/data/#road)
5. [芝加哥交通数据集](https://data.cityofchicago.org/Transportation/Taxi-Trips/wrvz-psew/data)
6. [Sioux-Falls Network](http://jlitraffic.appspot.com/tap.html)
7. [交通信号灯数据集](https://btsd.ethz.ch/shareddata/)
8. [KDD Cup'2019多模态交通推荐数据集-百度](https://dianshi.bce.baidu.com/competition/29/question)
9. [滴滴数据开放](https://outreach.didichuxing.com/research/opendata/)
10. [文本引用数据集](https://linqs.soe.ucsc.edu/data)
11. [机器之心数据集](https://www.jiqizhixin.com/sota)
12. [到达时间评估数据集-Kaggle交通数据集](https://www.kaggle.com/crailtap/taxi-trajectory)
13. [到达时间评估数据集](https://causlayer.orgs.hk/khaled-alkilane/GSTA)
14. [交通预测数据集](https://paperswithcode.com/task/traffic-prediction)
15. [交通数据集PeMS](https://dot.ca.gov/programs/traffic-operations/mpr/pems-source)
16. [丰富的数据集](https://zhuanlan.zhihu.com/p/119425995?utm_source=wechat_session&utm_medium=social&utm_oi=858349756462821376&utm_campaign=shareopn)

### Tool
1. [Openstreetmap](https://www.openstreetmap.org/#map=9/25.2744/110.3384)
2. [LibCity（阡陌）](https://github.com/LibCity/Bigscity-LibCity/blob/master/readme.md)
3. [LibCity视频解说](https://m.bilibili.com/video/BV1cS4y1d7hf?spm_id_from=333.999.0.0)
4. [LibCity的操作介绍](https://zhuanlan.zhihu.com/p/429494244)
5. [交通方面的工具](https://github.com/aptx1231/Traffic-Prediction-Open-Code-Summary)

### 好的推文
1. [如何做研究](https://mp.weixin.qq.com/s/gAsaa7fAraE5B-vm_izFTg?client=tim&ADUIN=727850024&ADSESSION=1577595981&ADTAG=CLIENT.QQ.5603_.0&ADPUBNO=26882)
2. [如何写论文](https://mp.weixin.qq.com/s/KiKObjQRCAIYl6twSj07rA)
3. [如何看论文](https://github.com/mli/paper-reading)
4. [吾辈楷模-10篇顶会paper，入选微软学者，上海交大吴齐天的科研思考！](https://mp.weixin.qq.com/s/QIXlqIFVhl0periVZiCo2A)
5. [搞科研，从好好读论文开始：沈向洋带你读论文了](https://mp.weixin.qq.com/s/E5glJ4rZX4OgmWyt9ERqcA)

### 学术工具
1. [中南大学图书馆](http://lib.csu.edu.cn/)
2. [超星发现](http://ss.zhizhen.com/)
3. [中国知网](https://www.cnki.net/)
4. [万方数据](http://www.wanfangdata.com.cn/index.html)
5. [百度学术](https://xueshu.baidu.com/)
6. [Google 学术](https://scholar.google.com/)
7. [Google 学术镜像](https://ac.scmor.com/)
8. [SCI-Hub](https://tool.yovisun.com/scihub/)
9. [Arxiv Sanity Preserver](http://www.arxiv-sanity.com/)
10. [arXiv](https://arxiv.org/)
11. [X-MOL](https://www.x-mol.com/)
12. [ZLibary--数字图书馆](https://1lib.limited/)
13. [科研通-文献求助网站](https://www.ablesci.com/)
14. [在线latex](https://www.overleaf.com/)
15. [文献管理mendeley](https://www.mendeley.com/download-reference-manager/)
16. [期刊分区查询](http://www.letpub.com.cn/index.php?page=journalapp)
17. [会议等级查询](https://www.ccf.org.cn/Academic_Evaluation/By_category/)
18. [语法检测工具grammarly](https://app.grammarly.com/)

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