---
title: "Flexible Data Fusion (and Fission)"
authors:
  - "Alexander S. Yeh"
doi: ""
url: "https://ijcai.org/proceedings/1985/81"
pdf: "https://ijcai.org/proceedings/1985/0081.pdf"
venue: "Proceedings of the Ninth International Joint Conference on Artificial Intelligence"
year: 1985
pages: "420-421"
track: "Expert Systems"
keywords:
---

# Flexible Data Fusion (and Fission)

Alexander S. Yeh

*Proceedings of the Ninth International Joint Conference on Artificial Intelligence*, pages 420-421.

## 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).