Utilizing Keywords Evolution in Context for Emerging Trend Detection in Scientific Publications-Reference-Cited by-同舟云学术

Utilizing Keywords Evolution in Context for Emerging Trend Detection in Scientific Publications

Published:2022-12 Issue: Volume: Page:
ISSN:
Container-title:The 11th International Symposium on Information and Communication Technology
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Author:

Nguyen Nhu Khoa¹^ORCID,Boros Emanuela²^ORCID,Lejeune Gaël³^ORCID,Doucet Antoine²^ORCID,Delahaut Thierry⁴^ORCID

Affiliation:

1. University of La Rochelle, L3i Laboratory, France and La Banque Postale Asset Management, France

2. University of La Rochelle, L3i Laboratory, France

3. Sorbonne University, STIH Laboratory, France

4. La Banque Postale Asset Management, France

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3568562.3568640

Reference31 articles.

1. End-to-end LDA-based automatic weak signal detection in web news

2. Automatic trend detection: Time-biased document clustering

3. Iz Beltagy Arman Cohan and Kyle Lo. 2019. SciBERT: Pretrained Contextualized Embeddings for Scientific Text. CoRR abs/1903.10676(2019). arXiv:1903.10676http://arxiv.org/abs/1903.10676 Iz Beltagy Arman Cohan and Kyle Lo. 2019. SciBERT: Pretrained Contextualized Embeddings for Scientific Text. CoRR abs/1903.10676(2019). arXiv:1903.10676http://arxiv.org/abs/1903.10676

4. Levent Bolelli Seyda Ertekin and C. Lee Giles. 2009. Topic and Trend Detection in Text Collections Using Latent Dirichlet Allocation. In ECIR. Levent Bolelli Seyda Ertekin and C. Lee Giles. 2009. Topic and Trend Detection in Text Collections Using Latent Dirichlet Allocation. In ECIR.

5. Qi Dang , Feng Gao , and Yadong Zhou . 2016. Early Detection Method for Emerging Topics Based on Dynamic Bayesian Networks in Micro-Blogging Networks. Expert Syst. Appl. 57 , C (Sept. 2016 ), 285–295. https://doi.org/10.1016/j.eswa.2016.03.050 10.1016/j.eswa.2016.03.050 Qi Dang, Feng Gao, and Yadong Zhou. 2016. Early Detection Method for Emerging Topics Based on Dynamic Bayesian Networks in Micro-Blogging Networks. Expert Syst. Appl. 57, C (Sept. 2016), 285–295. https://doi.org/10.1016/j.eswa.2016.03.050