Literatur SHKs
Überblick und Einführung: Cambria, E., & White, B. (2014). Jumping NLP curves: A review of natural language processing research. IEEE Computational intelligence magazine, 9(2), 48–57. Clark, A., Fox, C., & Lappin, S. (2013). The handbook of computational linguistics and natural language processing. John Wiley & Sons. Hirschberg, J., & Manning, C. D. (2015). Advances in natural language processing. Science, 349(6245), 261–266. Jones, D. B., & Somers, H. (2013). New Methods in Language Processing. Routledge. Jurafsky, D., & Martin, J. H. (2014). Speech and language processing (Bd. 3). Pearson London. Rapp, A. (2017). Manuelle und automatische Annotation. In F. Jannidis, H. Kohle, & M. Rehbein (Hrsg.), Digital Humanities (S. 253–267). Springer.
Für Latein / Antike: Jenset, G. B., & McGillivray, B. (2017). Quantitative Historical Linguistics: A Corpus Framework (Bd. 26). Oxford University Press. Johnson, K. P. (2016). Introduction to the Classical Language Toolkit. Abgerufen von https://ir.uiowa.edu/cgi/viewcontent.cgi?article=1020&context=bam McGillivray, B. (2013). Methods in Latin computational linguistics. Brill. McGillivray, B., & Kilgarriff, A. (2013). Tools for historical corpus research, and a corpus of Latin. New Methods in Historical Corpus Linguistics, 247–255.
Spezielle Tools: Bird, S., Klein, E., & Loper, E. (2009). Natural language processing with Python: analyzing text with the natural language toolkit. O’Reilly Media, Inc. Manning, C., Surdeanu, M., Bauer, J., Finkel, J., Bethard, S., & McClosky, D. (2014). The Stanford CoreNLP natural language processing toolkit. In Proceedings of 52nd annual meeting of the association for computational linguistics: system demonstrations (S. 55–60). Schweinberger, M. (2016). Part-Of-Speech Tagging with R. June. Straka, M., Hajic, J., & Straková, J. (2016). UDPipe: Trainable Pipeline for Processing CoNLL-U Files Performing Tokenization, Morphological Analysis, POS Tagging and Parsing. In LREC.