@InProceedings{kkedzia-piasecki-janz:2017:RANLP,
  author    = {K\k{e}dzia, Pawe{\l}  and  Piasecki, Maciej  and  Janz, Arkadiusz},
  title     = {Graph-Based Approach to Recognizing CST Relations in Polish Texts},
  booktitle = {Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP 2017},
  month     = {September},
  year      = {2017},
  address   = {Varna, Bulgaria},
  publisher = {INCOMA Ltd.},
  pages     = {363--371},
  abstract  = {This paper presents an supervised approach to the recognition of Cross-document
	Structure Theory (CST) relations in Polish texts.  In the proposed, graph-based
	representation is constructed for sentences. Graphs are built on the basis of
	lexicalised syntactic-semantic relation extracted from text. Similarity between
	sentences is calculated from graph, and the similarity values are input to
	classifiers trained by Logistic Model Tree. Several different configurations of
	graph, as well as graph similarity methods were analysed for this tasks. The
	approach was evaluated on a large open corpus annotated manually with 17 types
	of selected CST relations. The configuration of experiments was similar to
	those known from SEMEVAL and we obtained very promising results.},
  url       = {https://doi.org/10.26615/978-954-452-049-6_048}
}