{"type":"ScholarlyArticle","title":"A Dataset Complexity Measure for Analogical Transfer","authors":[{"name":"Fadi Badra","slug":"fadi-badra","given":"Fadi","family":"Badra","affiliation":"Université Sorbonne Paris Nord , Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances en e-Santé -LIMICS , INSERM , UMR 1142 , F-93000 , Bobigny , France"}],"abstract":"Analogical transfer consists in leveraging a measure of similarity between two situations to predict the amount of similarity between their outcomes. Acquiring a suitable similarity measure for analogical transfer may be difficult, especially when the data is sparse or when the domain knowledge is incomplete. To alleviate this problem, this paper presents a dataset complexity measure that can be used either to select an optimal similarity measure, or if the similarity measure is given, to perform analogical transfer: among the potential outcomes of a new situation, the most plausible is the one which minimizes the dataset complexity.","doi":"10.24963/ijcai.2020/222","url":"https://ijcai.org/proceedings/2020/222","pdf":"https://ijcai.org/proceedings/2020/0222.pdf","markdown":"https://ijcai.org/proceedings/2020/222.md","bibtex":"https://ijcai.org/proceedings/2020/bibtex/222","volume":{"slug":"2020","title":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2020","url":"https://ijcai.org/proceedings/2020/","year":2020,"location":"Yokohama","dates":"January 2021 (postponed from 11-17 July 2020)","editors":"Christian Bessiere","isbn":"978-0-9992411-6-5","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2020"},"section":"Knowledge Representation and Reasoning","track":"Main track","number":222,"pages":{"first":1601,"last":1607},"keywords":["Knowledge Representation and Reasoning: Case-based Reasoning","Knowledge Representation and Reasoning: Qualitative, Geometric, Spatial, Temporal Reasoning"],"videos":[{"label":"Video","url":"https://videos.ijcai20.org/24521/file_24521.m3u8","length_sec":273,"provider":"hls"}],"references":[{"position":1,"raw":"[Anthony and Ratsaby, 2015] Martin Anthony and Joel Ratsaby. 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