CURD: Context-aware Relevance and Urgency Determination-Reference-Cited by-同舟云学术

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CURD: Context-aware Relevance and Urgency Determination

Published:2024-07-10 Issue: Volume:14 Page:1-12
ISSN:
Container-title:Proceedings of the 36th International Conference on Scientific and Statistical Database Management
language:
Short-container-title:

Author:

Adesokan Ademola¹^ORCID,Madria Sanjay¹^ORCID

Affiliation:

1. Computer Science, Missouri University of Science and Technology, USA

Funder

National Science Foundation

The Kummer Institute for Student Success, Research, and Economic Development at the Missouri University of Science and Technology through the Kummer Innovation and Entrepreneurship Doctoral Fellowship.

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3676288.3676299

Reference41 articles.

1. NeuEmot: Mitigating Neutral Label and Reclassifying False Neutrals in the 2022 FIFA World Cup via Low-Level Emotion

2. HatEmoTweet: low-level emotion classifications and spatiotemporal trends of hate and offensive COVID-19 tweets

3. TweetACE: A Fine-grained Classification of Disaster Tweets using Transformer Model

4. Firoj Alam, Shafiq Joty, and Muhammad Imran. 2018. Domain Adaptation with Adversarial Training and Graph Embeddings. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). ACL, Melbourne, Australia, 1077–1087.

5. An Integrated Framework for Relevance Classification of Trending Topics in Arabic Tweets;Alkadri M.;International Journal of Advanced Computer Science and Applications,2023

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