{"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/kognac-efficient-encoding-of-large-knowledge","title":"KOGNAC: Efficient Encoding of Large Knowledge Graphs","arxiv_id":"1604.04795","date":"2016-04-16","proceeding":null,"authors":["Jacopo Urbani","Sourav Dutta","Sairam Gurajada","Gerhard Weikum"],"abstract":"Many Web applications require efficient querying of large Knowledge Graphs\n(KGs). We propose KOGNAC, a dictionary-encoding algorithm designed to improve\nSPARQL querying with a judicious combination of statistical and semantic\ntechniques. In KOGNAC, frequent terms are detected with a frequency\napproximation algorithm and encoded to maximise compression. Infrequent terms\nare semantically grouped into ontological classes and encoded to increase data\nlocality. We evaluated KOGNAC in combination with state-of-the-art RDF engines,\nand observed that it significantly improves SPARQL querying on KGs with up to\n1B edges.","url_abs":"http://arxiv.org/abs/1604.04795v2","url_pdf":"http://arxiv.org/pdf/1604.04795v2.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":"kognac-efficient-encoding-of-large-knowledge","repo_url":"https://github.com/jrbn/kognac","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"knowledge-graphs","task_name":"Knowledge Graphs"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}