{"type":"ScholarlyArticle","title":"Flexible Data Fusion (and Fission)","authors":[{"name":"Alexander S. Yeh","slug":"alexander-s-yeh","given":"Alexander S.","family":"Yeh","affiliation":""}],"abstract":"An approach is described for developing methods for \"data fusion\": given how events A & B occurring by themselves influence some measure, estimate the influence (on that measure) of A and B occurring together. An example is \"combine the effects of evidence on the belief (likelihood) of some hypothesis.\" This approach also deals with the opposite problem of estimating the effects on a measure of A and B by themselves when only their combined effects are known: data fission. The methods developed will both 1) try to make intuitive estimations at information not given, and 2) not conflict with any information given (unless it is inconsistent).","doi":null,"url":"https://ijcai.org/proceedings/1985/81","pdf":"https://ijcai.org/proceedings/1985/0081.pdf","markdown":"https://ijcai.org/proceedings/1985/81.md","bibtex":"https://ijcai.org/proceedings/1985/bibtex/81","volume":{"slug":"1985","title":"Proceedings of the Ninth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 1985","url":"https://ijcai.org/proceedings/1985/","year":1985,"location":"Los Angeles, California, USA","dates":"","editors":"Aravind Joshi","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":"Expert Systems","track":"Expert Systems","number":81,"pages":{"first":420,"last":421},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}