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Arezoo Hatefi Ghahfarrokhi

I am a Ph.D. student at the Industrial Doctoral School at Umeå University working on multimodal data analysis motivated by contextual advertising.




Works at

Affiliated as other position at Department of Computing Science
MIT-huset, Umeå universitet, MIT.B.436 Umeå universitet, 901 87 Umeå

I am a Ph.D. student in the Foundation of Language Processing Group. I started my Ph.D. in June 2019. My research is on the topic of multimodal semantic analysis for contextual advertising. Recently, I have focused on deep text clustering (using deep neural networks for clustering text documents such as news articles) and semi-supervised learning (learning from Unlabeled data, when used in conjunction with a small amount of labeled data) but my aim is to investigate clustering methods for multimodal data and zero/few-shot learning settings (which can simulate situations occurring in contextual advertising in the best way) further down the road. Using reinforcement learning to optimize clustering performance is also of special interest.

In general, my research interests are Natural Language Processing, Machine Learning (in particular Deep Learning), and Data Mining. During my master's thesis, I worked on sentiment analysis and I have also performed some research on natural language understanding and task-oriented dialogue systems before I started my Ph.D.

The 2024 joint international conference on computational linguistics, language resources and evaluation (LREC-COLING 2024), Torino, Italy, May 20-25, 2024
Hatefi, Arezoo; Eklund, Anton; Forsman, Mona
Proceedings of the 6th International Conference on Natural Language and Speech Processing (ICNLSP 2023), Association for Computational Linguistics 2023 : 68-77
Hatefi, Arezoo; Vu, Xuan-Son; Bhuyan, Monowar H.; et al.
CIKM '21: Proceedings of the 30th ACM International Conference on Information & Knowledge Management, ACM Digital Library 2021 : 3078-3082
Hatefi, Arezoo; Vu, Xuan-Son; Bhuyan, Monowar H.; et al.
SLTC 2020 – The Eighth Swedish Language Technology Conference, Online, November 25–27, 2020
Hatefi, Arezoo; Drewes, Frank
Hatefi, Arezoo; Björklund, Johanna; Vu, Xuan-Son; et al.

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