Fine-grained location prediction of non geo-tagged tweets

Author:

Abboud Mohammad1,Zeitouni Karine1,Taher Yehia1

Affiliation:

1. UVSQ - Université Paris-Saclay, Versailles, Yvelines, France

Funder

European Union?s Horizon 2020

H2020 EU GO GREEN ROUTES

Publisher

ACM

Reference24 articles.

1. Mohammad Abboud , Hafsa El Hafyani , Jingwei Zuo , Karine Zeitouni , and Yehia Taher . 2021 . Micro-environment Recognition in the context of Environmental Crowdsensing . Proceedings of the Workshops of the EDBT/ICDT 2021 Joint Conference 2841 (2021). Mohammad Abboud, Hafsa El Hafyani, Jingwei Zuo, Karine Zeitouni, and Yehia Taher. 2021. Micro-environment Recognition in the context of Environmental Crowdsensing. Proceedings of the Workshops of the EDBT/ICDT 2021 Joint Conference 2841 (2021).

2. Location-based and preference-aware recommendation using sparse geo-social networking data

3. Lianhua Chi , Kwan Hui Lim , Nebula Alam , and Christopher Butler . 2016 . Geolocation Prediction in Twitter Using Location Indicative Words and Textual Features . In Proceedings of the 2nd Workshop on Noisy User-generated Text (WNUT). The COLING 2016 Organizing Committee , Osaka, Japan. Lianhua Chi, Kwan Hui Lim, Nebula Alam, and Christopher Butler. 2016. Geolocation Prediction in Twitter Using Location Indicative Words and Textual Features. In Proceedings of the 2nd Workshop on Noisy User-generated Text (WNUT). The COLING 2016 Organizing Committee, Osaka, Japan.

4. Florina Dutt and Subhajit Das . 2021. Fine-grained Geolocation Prediction of Tweets with Human Machine Collaboration. arXiv preprint arXiv:2106.13411 ( 2021 ). Florina Dutt and Subhajit Das. 2021. Fine-grained Geolocation Prediction of Tweets with Human Machine Collaboration. arXiv preprint arXiv:2106.13411 (2021).

5. Multi-view stacking for activity recognition with sound and accelerometer data

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