@@ -11,3 +11,28 @@ This class provides methods for the calculation of different complexity metrics
-[examples.ipynb](examples.ipynb): Jupyter notebook that shows how to use the TextComplexityFreeling class in several testing texts.
-[texts/](texts/): Folder that contains all the testing texts used by the examples notebook.
# Citation
Please, if you use this library in your research, cite it as follows:
APA
López-Anguita, R., Collado-Montañez, J., & Montejo-Ráez, A. (2020). The Text Complexity Library. Procesamiento Del Lenguaje Natural, 65, 127-130. Recuperado de http://journal.sepln.org/sepln/ojs/ojs/index.php/pln/article/view/6289
BibTeX
```
@article{PLN6289,
author = {Rocío López-Anguita y Jaime Collado-Montañez y Arturo Montejo-Ráez},
title = {The Text Complexity Library},
journal = {Procesamiento del Lenguaje Natural},
volume = {65},
number = {0},
year = {2020},
keywords = {},
abstract = {This paper introduces a new resource for computing textual complexity. It consists in a Python library for calculating different complexity metrics for several languages from plain texts. The resource has been made available to the research community and provides all needed instructions for its installation and use. To our knowledge, it is the first time a resource like this is published, so we expect many researchers can profit from it.},
