IncompFuse: a logical framework for historical information fusion with inaccurate data sources

作者:Jiawei Xu, Vladimir Zadorozhny, John Grant

摘要

We propose a novel framework, called IncompFuse, that significantly improves the accuracy of existing methods for reconstructing aggregated historical data from inaccurate historical reports. IncompFuse supports efficient data reliability assessment using the incompatibility probability of historical reports. We provide a systematic approach to define this probability based on properties of the data and relationships between the reports. Our experimental study demonstrates high utility of the proposed framework. In particular, we were able to detect noisy historical reports with very high detection accuracy.

论文关键词:Inaccurate data sources, Incompatibility probability, Error detection

论文评审过程:

论文官网地址:https://doi.org/10.1007/s10844-019-00569-6