Unveiling Comparative Sentiments in Vietnamese Product Reviews: A Sequential Classification Framework

Autor:	Le, Ha, Tran, Bao, Le, Phuong, Nguyen, Tan, Nguyen, Dac, Pham, Ngoan, Huynh, Dang
Rok vydání:	2024
Předmět:	Computer Science - Computation and Language
Druh dokumentu:	Working Paper
Popis:	Comparative opinion mining is a specialized field of sentiment analysis that aims to identify and extract sentiments expressed comparatively. To address this task, we propose an approach that consists of solving three sequential sub-tasks: (i) identifying comparative sentence, i.e., if a sentence has a comparative meaning, (ii) extracting comparative elements, i.e., what are comparison subjects, objects, aspects, predicates, and (iii) classifying comparison types which contribute to a deeper comprehension of user sentiments in Vietnamese product reviews. Our method is ranked fifth at the Vietnamese Language and Speech Processing (VLSP) 2023 challenge on Comparative Opinion Mining (ComOM) from Vietnamese Product Reviews. Comment: Accepted manuscript at VLSP 2023
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2401.01108 Zobrazit plný text záznamu View this record from Arxiv