{"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/fast-linear-model-for-knowledge-graph","title":"Fast Linear Model for Knowledge Graph Embeddings","arxiv_id":"1710.10881","date":"2017-10-30","proceeding":null,"authors":["Armand Joulin","Edouard Grave","Piotr Bojanowski","Maximilian Nickel","Tomas Mikolov"],"abstract":"This paper shows that a simple baseline based on a Bag-of-Words (BoW)\nrepresentation learns surprisingly good knowledge graph embeddings. By casting\nknowledge base completion and question answering as supervised classification\nproblems, we observe that modeling co-occurences of entities and relations\nleads to state-of-the-art performance with a training time of a few minutes\nusing the open sourced library fastText.","url_abs":"http://arxiv.org/abs/1710.10881v1","url_pdf":"http://arxiv.org/pdf/1710.10881v1.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":"fast-linear-model-for-knowledge-graph","repo_url":"https://github.com/facebookresearch/fastText","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"knowledge-base-completion","task_name":"Knowledge Base Completion"},{"task_slug":"knowledge-graph-embeddings","task_name":"Knowledge Graph Embeddings"},{"task_slug":"question-answering","task_name":"Question Answering"},{"task_slug":"model","task_name":"model"}],"methods":[{"method_slug":"fasttext","method_name":"fastText"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1710.10881","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}