Maximum Entropy in Support of Semantically Annotated Datasets

Publication Year:
2008
Usage 164
Downloads 139
Abstract Views 25
Repository URL:
https://digitalcommons.utep.edu/cs_techrep/112
Author(s):
Pinheiro da Silva, Paulo; Kreinovich, Vladik; Servin, Christian
Tags:
semantic web; ontology; uncertainty; probabilistic ap- proach; Maximum Entropy approach; Computer Engineering
article description
One of the important problems of semantic web is checking whether two datasets describe the same quantity. The existing solution to this problem is to use these datasets' ontologies to deduce that these datasets indeed represent the same quantity. However, even when ontologies seem to confirm the identify of the two corresponding quantities, it is still possible that in reality, we deal with somewhat different quantities. A natural way to check the identity is to compare the numerical values of the measurement results: if they are close (within measurement errors), then most probably we deal with the same quantity, else we most probably deal with different ones. In this paper, we show how to perform this checking.