@inproceedings{annas-siagian-2025-anaselka,
title = "Anaselka at {S}em{E}val-2025 Task 9: Leveraging {SVM} and {MNB} for Detecting Food Hazard",
author = "Annas, Anwar and
Siagian, Al Hafiz",
editor = "Rosenthal, Sara and
Ros{\'a}, Aiala and
Ghosh, Debanjan and
Zampieri, Marcos",
booktitle = "Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025)",
month = jul,
year = "2025",
address = "Vienna, Austria",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.semeval-1.111/",
pages = "807--811",
ISBN = "979-8-89176-273-2",
abstract = "Our system for the Sub-task 1 of SemEval-2025 Task 9 has been designed to tackle the complexities of identifying and categorizing food safety incidents from textual data. Through a rigorous experimental setup, we have developed a text classification solution that leveraged state-of-the-art techniques in data preprocessing, feature engineering, and model optimization."
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%0 Conference Proceedings
%T Anaselka at SemEval-2025 Task 9: Leveraging SVM and MNB for Detecting Food Hazard
%A Annas, Anwar
%A Siagian, Al Hafiz
%Y Rosenthal, Sara
%Y Rosá, Aiala
%Y Ghosh, Debanjan
%Y Zampieri, Marcos
%S Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025)
%D 2025
%8 July
%I Association for Computational Linguistics
%C Vienna, Austria
%@ 979-8-89176-273-2
%F annas-siagian-2025-anaselka
%X Our system for the Sub-task 1 of SemEval-2025 Task 9 has been designed to tackle the complexities of identifying and categorizing food safety incidents from textual data. Through a rigorous experimental setup, we have developed a text classification solution that leveraged state-of-the-art techniques in data preprocessing, feature engineering, and model optimization.
%U https://aclanthology.org/2025.semeval-1.111/
%P 807-811
Markdown (Informal)
[Anaselka at SemEval-2025 Task 9: Leveraging SVM and MNB for Detecting Food Hazard](https://aclanthology.org/2025.semeval-1.111/) (Annas & Siagian, SemEval 2025)
ACL