@inproceedings{a0b9a6b2b5ec4742874ea94cd3003963,
title = "Using ontologies to query probabilistic numerical data",
abstract = "We consider ontology-based query answering in a setting where some of the data are numerical and of a probabilistic nature, such as data obtained from uncertain sensor readings. The uncertainty for such numerical values can be more precisely represented by continuous probability distributions than by discrete probabilities for numerical facts concerning exact values. For this reason, we extend existing approaches using discrete probability distributions over facts by continuous probability distributions over numerical values. We determine the exact (data and combined) complexity of query answering in extensions of the well-known description logics εL and ALC with numerical comparison operators in this probabilistic setting.",
author = "Franz Baader and Patrick Koopmann and Anni-Yasmin Turhan",
year = "2017",
doi = "10.1007/978-3-319-66167-4\_5",
language = "English",
isbn = "9783319661667",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "77--94",
editor = "C. Dixon and M. Finger",
booktitle = "Frontiers of Combining Systems - 11th International Symposium, FroCoS 2017, Proceedings",
note = "11th International Symposium on Frontiers of Combining Systems, FroCoS 2017 ; Conference date: 27-09-2017 Through 29-09-2017",
}