Summary of the paper

Title PyRATA, Python Rule-based feAture sTructure Analysis
Authors Nicolas Hernandez and Amir Hazem
Abstract In this paper, we present a new Python 3 module named PyRATA, which stands for ”Python Rule-based feAture sTructure Analysis”. The module is released under the Apache V2 license. It aims at supporting rules-based analysis on structured data. PyRATA offers a language expressiveness which covers the functionalities of all the concurrent modules and more. Designed to be intuitive, the pattern syntax and the engine API follow existing standard definitions; Respectively Perl regular expression syntax and Python re module API. Using a simple native Python data structure (i.e. sequence of feature sets) allows it to deal with various kinds of data (textual or not) at various levels, such as a list of words, a list of sentences, a list of posts of a forum thread, a list of events of a calendar... This specificity makes it free from any (linguistic) process.
Topics Text Mining, Information Extraction, Information Retrieval, Tools, Systems, Applications
Full paper PyRATA, Python Rule-based feAture sTructure Analysis
Bibtex @InProceedings{HERNANDEZ18.732,
  author = {Nicolas Hernandez and Amir Hazem},
  title = "{PyRATA, Python Rule-based feAture sTructure Analysis}",
  booktitle = {Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)},
  year = {2018},
  month = {May 7-12, 2018},
  address = {Miyazaki, Japan},
  editor = {Nicoletta Calzolari (Conference chair) and Khalid Choukri and Christopher Cieri and Thierry Declerck and Sara Goggi and Koiti Hasida and Hitoshi Isahara and Bente Maegaard and Joseph Mariani and Hélène Mazo and Asuncion Moreno and Jan Odijk and Stelios Piperidis and Takenobu Tokunaga},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {979-10-95546-00-9},
  language = {english}
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