{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/aspect-category-opinion-sentiment-extraction","title":"Aspect-Category-Opinion-Sentiment Extraction Using Generative Transformer Model","arxiv_id":null,"date":"2023-01-18","proceeding":"RIFV 2023 1","authors":["Cao Duy Hoang","Quang Vinh Dinh","Ngoc Hong Tran"],"abstract":"Sentiment analysis is one of Natural Language Processing's applications that aims to process and extract sentiment information quickly and effectively. To expand upon the previous triplet extraction, that being aspect-opinion-sentiment triplets, Aspect-Category-Opinion-Sentiment (ACOS) quadruple extraction was created. There are several methods to extract quadruples, albeit with several limitations, such as their effectiveness towards implicit information and their overall low-performance score. This paper proposes a method of using BART-Aspect-Based-Sentiment-Analysis (BARTABSA), a sentiment analysis model that aims to unify the previous Aspect Based Sentiment Analysis subtask - namely Aspect-Opinion pair extraction and Aspect-Opinion-Sentiment triplet extraction, and solve them without changing the core algorithm or adding other models to it - to solve the ACOS subtask. After some modification to the data and the model's outer layer, the result shows significant and promising improvements over previous results.","url_abs":"https://ieeexplore.ieee.org/document/10013820","url_pdf":"https://ieeexplore.ieee.org/document/10013820","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"aspect-category-opinion-sentiment-extraction","repo_url":"https://github.com/TomtheCodeBot/Sentiment-Analysis","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"aspect-based-sentiment-analysis-1","task_name":"Aspect-Based Sentiment Analysis"},{"task_slug":"aspect-based-sentiment-analysis","task_name":"Aspect-Based Sentiment Analysis (ABSA)"},{"task_slug":"aspect-category-opinion-sentiment-quadruple","task_name":"Aspect-Category-Opinion-Sentiment Quadruple Extraction"},{"task_slug":"sentiment-analysis","task_name":"Sentiment Analysis"},{"task_slug":null,"task_name":"Triplet"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/aspect-category-opinion-sentiment-quadruple-1","task":"Aspect-Category-Opinion-Sentiment Quadruple Extraction","dataset":"Laptop-ACOS","model":"BART-ABSA","rank_in_archive_order":2,"of":2,"metrics":{"F1":"39.41"},"uses_additional_data":false},{"leaderboard":"/sota/aspect-category-opinion-sentiment-quadruple","task":"Aspect-Category-Opinion-Sentiment Quadruple Extraction","dataset":"Restaurant-ACOS","model":"BART-ABSA","rank_in_archive_order":2,"of":2,"metrics":{"F1":"53.45"},"uses_additional_data":false}],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}