@article {853, title = {Counterfactual reasoning over large-scale human performance optimization experiments}, journal = {Virtual poster presented at the annual meeting of the Psychonomic Society, November 2020}, year = {2020}, author = {Ion Juvina and William R. Aue and Brandon Minnery and Pascal Hitzler and Srikanth Nadella and Md Kamruzzaman Sarker} } @conference {813, title = {Wikipedia Knowledge Graph for Explainable AI}, booktitle = {Second Iberoamerican Knowledge Graphs and Semantic Web Conference (KGSWC)}, year = {2020}, month = {11/2020}, abstract = {

Explainable artificial intelligence (XAI) requires domain information to explain a system{\textquoteright}s decisions, for which structured forms of domain information like Knowledge Graphs (KGs) or ontologies are best suited. As such, readily available KGs are important to accelerate progress in XAI. To facilitate the advancement of XAI, we present the Wikipedia Knowledge Graph (WKG), based on information from English Wikipedia. Each Wikipedia article title, its corresponding category, and the category hierarchy are transformed into different entities in the knowledge graph. As the Wikipedia category hierarchy is not a tree, instead forming a graph, to make the finding process of the parent category easier, we break cycles in the category hierarchy. We evaluate whether the WKG is helpful to improve XAI compared with existing KGs, finding that WKG is better suited than the current state of the art. We also compare the cycle-free WKG with the Suggested Upper Merged Ontology (SUMO) and DBpedia schema KGs, finding minimal to no information loss.

}, author = {Md Kamruzzaman Sarker and Joshua Schwartz and Pascal Hitzler and Lu Zhou and Srikanth Nadella and Brandon Minnery and Ion Juvina and Michael L. Raymer and William R. Aue} }