TECHNOLOGY FOR CREATING A COMPUTER PROGRAM FOR DETECTING PUNCTUATION ERRORS
Keywords:
linguistics, information technology, morphological, syntactic and semantic aspectsAbstract
This article provides general information about the technology of creating a computer program that detects punctuation errors, and it is emphasized that the detection and correction of punctuation errors is important not only for the grammatical correctness of the language, but also for the intelligibility and communicative effectiveness of the text. It is also explained that punctuation error detection software can serve as an important addition to various text analysis platforms and applications.
References
1. Jurafsky, D., & Martin, J. H. (2019). Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition. Nashriyot: Pearson. ISBN: 978-0131873216
2. Manning, C. D., & Schütze, H. (1999). Foundations of Statistical Natural Language Processing. Nashriyot: MIT Press. ISBN: 978-0262133609
3. Goldberg, Y. (2017). Neural Network Methods for Natural Language Processing. Nashriyot: Morgan & Claypool Publishers. ISBN: 978-1627052986
4. Charniak, E. (1993). Statistical Language Learning. Nashriyot: MIT Press. ISBN: 978-0262033039
5. Briscoe, T. (1996). Automatic Extraction of Grammar from Corpora. Nashriyot: MIT Press. ISBN: 978-0262527330
6. Lison, P., & Tiedemann, J. (2016). OpenSubtitles2016: Extracting Large Parallel Corpora from Movie and TV Subtitles.Nashriyot: LREC Proceedings.
7. Andrej Karpathy (2015). The Unreasonable Effectiveness of Recurrent Neural Networks. Onlayn manba: http://karpathy.github.io/2015/05/21/rnn-effectiveness/
8. Genzel, D., & Charniak, E. (2002). Entropy Rate Constancy in Text. Nashriyot: Association for Computational Linguistics (ACL)
9. Bird, S., Klein, E., & Loper, E. (2009). Natural Language Processing with Python. Nashriyot: O'Reilly Media. ISBN: 978-0596516499
