Multi-label classification is rapidly developing as an important aspect of modern predictive modeling. In this paper, we propose a multi-label text classification approach in order to extract the labels of economic concepts from economic news articles. We demonstrate a multi-label sentence-level event classification with a multi-label classifier algorithm. The classifier uses BERT Model and classification based on the association between labels via a threshold. The experiment on real-world multi-label data with many labels demonstrates an appealing performance and efficiency of multi-label classification.
|Title of host publication||ICUFN 2022 - 13th International Conference on Ubiquitous and Future Networks|
|Publisher||IEEE Computer Society|
|Number of pages||4|
|Publication status||Published - 2022|
|Event||13th International Conference on Ubiquitous and Future Networks, ICUFN 2022 - Virtual, Barcelona, Spain|
Duration: 2022 Jul 5 → 2022 Jul 8
|Name||International Conference on Ubiquitous and Future Networks, ICUFN|
|Conference||13th International Conference on Ubiquitous and Future Networks, ICUFN 2022|
|Period||22/7/5 → 22/7/8|
Bibliographical noteFunding Information:
This research was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. NRF-2J21R1F1A1J5JM77) and (NRF-2J22R1A2C2JJ4JJ3) Correspondence should be addressed to email@example.com.
© 2022 IEEE.
- Multi-label Classification
- Natural Language Processing
- Text Classification
ASJC Scopus subject areas
- Computer Networks and Communications
- Computer Science Applications
- Hardware and Architecture