<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Chlebowski, Szymon</style></author><author><style face="normal" font="default" size="100%">Maciej Komosinski</style></author><author><style face="normal" font="default" size="100%">Adam Kups</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Automated Generation of Erotetic Search Scenarios: Classification, Optimization, and Knowledge Extraction</style></title><secondary-title><style face="normal" font="default" size="100%">ACM Transactions on Computational Logic</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">knowledge extraction</style></keyword><keyword><style  face="normal" font="default" size="100%">Logic of questions</style></keyword><keyword><style  face="normal" font="default" size="100%">multicriteria analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">optimal erotetic scenario</style></keyword><keyword><style  face="normal" font="default" size="100%">rule mining</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2017</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.cs.put.poznan.pl/mkomosinski/research/automated-erotetic-search-scenarios.pdf</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">2</style></number><publisher><style face="normal" font="default" size="100%">ACM</style></publisher><pub-location><style face="normal" font="default" size="100%">New York</style></pub-location><volume><style face="normal" font="default" size="100%">18</style></volume><pages><style face="normal" font="default" size="100%">8:1–8:27</style></pages><abstract><style face="normal" font="default" size="100%">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.</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue></record></records></xml>