{"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/ad3-attentive-deep-document-dater","title":"AD3: Attentive Deep Document Dater","arxiv_id":"1902.02161","date":"2019-01-21","proceeding":"EMNLP 2018 10","authors":["Swayambhu Nath Ray","Shib Sankar Dasgupta","Partha Talukdar"],"abstract":"Knowledge of the creation date of documents facilitates several tasks such as\nsummarization, event extraction, temporally focused information extraction etc.\nUnfortunately, for most of the documents on the Web, the time-stamp metadata is\neither missing or can't be trusted. Thus, predicting creation time from\ndocument content itself is an important task. In this paper, we propose\nAttentive Deep Document Dater (AD3), an attention-based neural document dating\nsystem which utilizes both context and temporal information in documents in a\nflexible and principled manner. We perform extensive experimentation on\nmultiple real-world datasets to demonstrate the effectiveness of AD3 over\nneural and non-neural baselines.","url_abs":"http://arxiv.org/abs/1902.02161v1","url_pdf":"http://arxiv.org/pdf/1902.02161v1.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":"ad3-attentive-deep-document-dater","repo_url":"https://github.com/malllabiisc/AD3","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"tf","reach":null}],"tasks":[{"task_slug":"document-dating","task_name":"Document Dating"},{"task_slug":"event-extraction","task_name":"Event Extraction"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}