{"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-term-extraction-with-history-attention","title":"Aspect Term Extraction with History Attention and Selective Transformation","arxiv_id":"1805.00760","date":"2018-05-02","proceeding":null,"authors":["Xin Li","Lidong Bing","Piji Li","Wai Lam","Zhimou Yang"],"abstract":"Aspect Term Extraction (ATE), a key sub-task in Aspect-Based Sentiment\nAnalysis, aims to extract explicit aspect expressions from online user reviews.\nWe present a new framework for tackling ATE. It can exploit two useful clues,\nnamely opinion summary and aspect detection history. Opinion summary is\ndistilled from the whole input sentence, conditioned on each current token for\naspect prediction, and thus the tailor-made summary can help aspect prediction\non this token. Another clue is the information of aspect detection history, and\nit is distilled from the previous aspect predictions so as to leverage the\ncoordinate structure and tagging schema constraints to upgrade the aspect\nprediction. Experimental results over four benchmark datasets clearly\ndemonstrate that our framework can outperform all state-of-the-art methods.","url_abs":"http://arxiv.org/abs/1805.00760v1","url_pdf":"http://arxiv.org/pdf/1805.00760v1.pdf","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-term-extraction-with-history-attention","repo_url":"https://github.com/lixin4ever/HAST","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":{"status":"ok"}}],"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":"prediction","task_name":"Prediction"},{"task_slug":"sentence","task_name":"Sentence"},{"task_slug":"sentiment-analysis","task_name":"Sentiment Analysis"},{"task_slug":"term-extraction","task_name":"Term Extraction"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1805.00760","atlas_url":"https://app.syntology.ai/?focus=1805.00760","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}