{"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/using-multi-label-classification-for-improved","title":"Using Multi-Label Classification for Improved Question Answering","arxiv_id":"1710.08634","date":"2017-10-24","proceeding":null,"authors":["Ricardo Usbeck","Michael Hoffmann","Michael Röder","Jens Lehmann","Axel-Cyrille Ngonga Ngomo"],"abstract":"A plethora of diverse approaches for question answering over RDF data have\nbeen developed in recent years. While the accuracy of these systems has\nincreased significantly over time, most systems still focus on particular types\nof questions or particular challenges in question answering. What is a curse\nfor single systems is a blessing for the combination of these systems. We show\nin this paper how machine learning techniques can be applied to create a more\naccurate question answering metasystem by reusing existing systems. In\nparticular, we develop a multi-label classification-based metasystem for\nquestion answering over 6 existing systems using an innovative set of 14\nquestion features. The metasystem outperforms the best single system by 14%\nF-measure on the recent QALD-6 benchmark. Furthermore, we analyzed the\ninfluence and correlation of the underlying features on the metasystem quality.","url_abs":"http://arxiv.org/abs/1710.08634v1","url_pdf":"http://arxiv.org/pdf/1710.08634v1.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":"using-multi-label-classification-for-improved","repo_url":"https://github.com/dice-group/NLIWOD/tree/master/qa.ml","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"classification-1","task_name":"Classification"},{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"multi-label-classification-2","task_name":"MUlTI-LABEL-ClASSIFICATION"},{"task_slug":"multi-label-classification","task_name":"Multi-Label Classification"},{"task_slug":"question-answering","task_name":"Question Answering"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1710.08634","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}