@proceedings {770,
	title = {Completion Reasoning Emulation for the Description Logic EL+},
	journal = {Proceedings of the AAAI 2020 Spring Symposium on Combining Machine Learning and Knowledge Engineering in Practice},
	volume = {2600},
	year = {2020},
	month = {03/2020},
	publisher = {CEUR-WS.org},
	address = {Stanford University, Palo Alto, California, USA},
	abstract = {<p>We present a new approach to integrating deep learning with knowledge-based systems that we believe shows promise. Our approach seeks to emulate reasoning structure, which can be inspected part-way through, rather than simply learning reasoner answers, which is typical in many of the black-box systems currently in use. We demonstrate that this idea is feasible by training a long short-term memory (LSTM) artificial neural network to learn EL+ reasoning patterns with two different data sets. We also show that this trained system is resistant to noise by corrupting a percentage of the test data and comparing the reasoner{\textquoteright}s and LSTM{\textquoteright}s predictions on corrupt data with correct answers.</p>
},
	keywords = {Deep Learning, Description Logic, EL+, LSTM, NeSy, Reasoning},
	url = {http://ceur-ws.org/Vol-2600/paper5.pdf},
	author = {Aaron Eberhart and Monireh Ebrahimi and Lu Zhou and Cogan Shimizu and Pascal Hitzler}
}
@conference {610,
	title = {A Modification to the Hazardous Situation ODP to Support Risk Assessment and Mitigation},
	booktitle = {Workshop on Ontology Design Patterns (WOP)},
	year = {2016},
	month = {10/2016},
	abstract = {<p>The Hazardous Situation ontology design pattern models the consequences of exposure of an object to a hazard. In its current form, the ODP is well suited for representing the consequences of exposure after the fact, which is very useful for applications such as damage assessment and recovery planning. In this work, we present a modification to this pattern that enables it to additionally support proactive questions central to risk assessment and mitigation planning.</p>
},
	keywords = {hazard, Ontology Design Pattern, risk assessment, risk mitigation},
	author = {Michelle Cheatham and Ferguson, Holly and Charles, Vardeman and Cogan Shimizu}
}
