@article {Chlebowski-et-al-2017,
	title = {Automated Generation of Erotetic Search Scenarios: Classification, Optimization, and Knowledge Extraction},
	journal = {ACM Transactions on Computational Logic},
	volume = {18},
	number = {2},
	year = {2017},
	pages = {8:1{\textendash}8:27},
	publisher = {ACM},
	address = {New York},
	abstract = {This paper concerns automated generation and processing of erotetic search scenarios (ESSs). ESSs are formal constructs characterized in Inferential Erotetic Logic that enable finding possible answers to a posed question by decomposing it into auxiliary questions. The first part of this work describes a formal account on ESSs. The formal approach is then applied to automatically generate ESSs, and the resulting scenarios are evaluated according to a number of criteria. These criteria are subjected to discordance analysis that reveals their mutual relationships. Finally, knowledge concerning relationships between different values of evaluation criteria is extracted by applying Apriori - an association rules mining algorithm. The proposed approach of integration of formal erotetic logic with computational tools provides an extensive insight into the former and helps with the development of efficient ESSs.},
	keywords = {knowledge extraction, Logic of questions, multicriteria analysis, optimal erotetic scenario, rule mining},
	issn = {1529-3785},
	doi = {10.1145/3056537},
	url = {http://www.cs.put.poznan.pl/mkomosinski/research/automated-erotetic-search-scenarios.pdf},
	author = {Chlebowski, Szymon and Maciej Komosinski and Adam Kups}
}
