@InProceedings{tajner-hulpus:2018:C18-1,
  author    = {Štajner, Sanja  and  Hulpus, Ioana},
  title     = {Automatic Assessment of Conceptual Text Complexity Using Knowledge Graphs},
  booktitle = {Proceedings of the 27th International Conference on Computational Linguistics},
  month     = {August},
  year      = {2018},
  address   = {Santa Fe, New Mexico, USA},
  publisher = {Association for Computational Linguistics},
  pages     = {318--330},
  abstract  = {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.},
  url       = {http://www.aclweb.org/anthology/C18-1027}
}