{"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/know-evolve-deep-temporal-reasoning-for","title":"Know-Evolve: Deep Temporal Reasoning for Dynamic Knowledge Graphs","arxiv_id":"1705.05742","date":"2017-05-16","proceeding":"ICML 2017 8","authors":["Rakshit Trivedi","Hanjun Dai","Yichen Wang","Le Song"],"abstract":"The availability of large scale event data with time stamps has given rise to\ndynamically evolving knowledge graphs that contain temporal information for\neach edge. Reasoning over time in such dynamic knowledge graphs is not yet well\nunderstood. To this end, we present Know-Evolve, a novel deep evolutionary\nknowledge network that learns non-linearly evolving entity representations over\ntime. The occurrence of a fact (edge) is modeled as a multivariate point\nprocess whose intensity function is modulated by the score for that fact\ncomputed based on the learned entity embeddings. We demonstrate significantly\nimproved performance over various relational learning approaches on two large\nscale real-world datasets. Further, our method effectively predicts occurrence\nor recurrence time of a fact which is novel compared to prior reasoning\napproaches in multi-relational setting.","url_abs":"http://arxiv.org/abs/1705.05742v3","url_pdf":"http://arxiv.org/pdf/1705.05742v3.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":"know-evolve-deep-temporal-reasoning-for","repo_url":"https://github.com/rstriv/Know-Evolve","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":{"status":"ok"}},{"paper_slug":"know-evolve-deep-temporal-reasoning-for","repo_url":"https://github.com/INK-USC/RE-Net","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"entity-embeddings","task_name":"Entity Embeddings"},{"task_slug":"knowledge-graphs","task_name":"Knowledge Graphs"},{"task_slug":"relational-reasoning","task_name":"Relational Reasoning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=1705.05742","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}