%0 Conference Proceedings %T Automatic Assessment of Conceptual Text Complexity Using Knowledge Graphs %A Štajner, Sanja %A Hulpuş, Ioana %Y Bender, Emily M. %Y Derczynski, Leon %Y Isabelle, Pierre %S Proceedings of the 27th International Conference on Computational Linguistics %D 2018 %8 August %I Association for Computational Linguistics %C Santa Fe, New Mexico, USA %F stajner-hulpus-2018-automatic %X Complexity of texts is usually assessed only at the lexical and syntactic levels. Although it is known that conceptual complexity plays a significant role in text understanding, no attempts have been made at assessing it automatically. We propose to automatically estimate the conceptual complexity of texts by exploiting a number of graph-based measures on a large knowledge base. By using a high-quality language learners corpus for English, we show that graph-based measures of individual text concepts, as well as the way they relate to each other in the knowledge graph, have a high discriminative power when distinguishing between two versions of the same text. Furthermore, when used as features in a binary classification task aiming to choose the simpler of two versions of the same text, our measures achieve high performance even in a default setup. %U https://aclanthology.org/C18-1027 %P 318-330