Recent Advances in Querying Probabilistic Knowledge Bases
Abstract
We give a survey on recent advances at the forefront of research on probabilistic knowledge bases for representing and querying large-scale automatically extracted data. We concentrate especially on increasing the semantic expressivity of formalisms for representing and querying probabilistic knowledge (i) by giving up the closed-world assumption, (ii) by allowing for commonsense knowledge (and in parallel giving up the tuple-independence assumption), and (iii) by giving up the closed-domain assumption, while preserving some computational properties of query answering in such formalisms.
Cite
Text
Borgwardt et al. "Recent Advances in Querying Probabilistic Knowledge Bases." International Joint Conference on Artificial Intelligence, 2018. doi:10.24963/IJCAI.2018/765Markdown
[Borgwardt et al. "Recent Advances in Querying Probabilistic Knowledge Bases." International Joint Conference on Artificial Intelligence, 2018.](https://mlanthology.org/ijcai/2018/borgwardt2018ijcai-recent/) doi:10.24963/IJCAI.2018/765BibTeX
@inproceedings{borgwardt2018ijcai-recent,
title = {{Recent Advances in Querying Probabilistic Knowledge Bases}},
author = {Borgwardt, Stefan and Ceylan, Ismail Ilkan and Lukasiewicz, Thomas},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2018},
pages = {5420-5426},
doi = {10.24963/IJCAI.2018/765},
url = {https://mlanthology.org/ijcai/2018/borgwardt2018ijcai-recent/}
}