bibliography.bib

@inproceedings{networks,
    author = {Batcher, Kenneth},
    year = {1968},
    month = {01},
    pages = {307-314},
    title = {Sorting networks and their applications},
    volume = {32},
    journal = {Proceed. AFIPS Spring Joint Comput. Conf.},
    doi = {10.1145/1468075.1468121}
}

@misc{bitonic,
   author = {Nikos Pitsianis},
   title = {bitonic.c code snippet},
   year = {2008},
   url = {https://courses.cs.duke.edu//fall08/cps196.1/Pthreads/bitonic.c},
   note = {{Online}, {accessed 19-02-2022}}
}

@article{4way_radix,
    author = {Ha, Linh and Krüger, Jens and Silva, Claudio},
    year = {2009},
    month = {12},
    pages = {2368-2378},
    title = {Fast 4-way parallel radix sorting on GPUs},
    volume = {28},
    journal = {Comput. Graph. Forum},
    doi = {10.1111/j.1467-8659.2009.01542.x}
}

@article{parallel_algos,
    author = {Hillis, W. Daniel and Steele, Guy L.},
    title = {Data Parallel Algorithms},
    year = {1986},
    issue_date = {Dec. 1986},
    publisher = {Association for Computing Machinery},
    address = {New York, NY, USA},
    volume = {29},
    number = {12},
    issn = {0001-0782},
    url = {https://doi.org/10.1145/7902.7903},
    doi = {10.1145/7902.7903},
    abstract = {Parallel computers with tens of thousands of processors are typically programmed in a data parallel style, as opposed to the control parallel style used in multiprocessing. The success of data parallel algorithms—even on problems that at first glance seem inherently serial—suggests that this style of programming has much wider applicability than was previously thought.},
    journal = {Commun. ACM},
    month = {dec},
    pages = {1170–1183},
    numpages = {14}
}

@Manual{R,
    title = {R: A Language and Environment for Statistical Computing},
    author = {{R Core Team}},
    organization = {R Foundation for Statistical Computing},
    address = {Vienna, Austria},
    year = {2021},
    url = {https://www.R-project.org/},
  }

@Manual{Rmd,
    title = {rmarkdown: Dynamic Documents for R},
    author = {JJ Allaire and Yihui Xie and Jonathan McPherson and Javier Luraschi and Kevin Ushey and Aron Atkins and Hadley Wickham and Joe Cheng and Winston Chang and Richard Iannone},
    year = {2021},
    note = {R package version 2.11},
    url = {https://github.com/rstudio/rmarkdown},
}

@Book{RmdDG,
    title = {R Markdown: The Definitive Guide},
    author = {Yihui Xie and J.J. Allaire and Garrett Grolemund},
    publisher = {Chapman and Hall/CRC},
    address = {Boca Raton, Florida},
    year = {2018},
    note = {ISBN 9781138359338},
    url = {https://bookdown.org/yihui/rmarkdown},
}

@Book{RmdCB,
    title = {R Markdown Cookbook},
    author = {Yihui Xie and Christophe Dervieux and Emily Riederer},
    publisher = {Chapman and Hall/CRC},
    address = {Boca Raton, Florida},
    year = {2020},
    note = {ISBN 9780367563837},
    url = {https://bookdown.org/yihui/rmarkdown-cookbook},
}

@misc{wooorm/dictionaries,
   author = {Titus Wormer},
   title = {dictionaries git repository},
   url = {https://github.com/wooorm/dictionaries},
   note = {{Online}, {accessed 20-12-2021}}
}

@misc{g4g,
   author = {geeksforgeeks.org},
   title = {Correcting Words using NLTK in Python},
   url = {https://www.geeksforgeeks.org/correcting-words-using-nltk-in-python/},
   note = {{Online}, {accessed 20-12-2021}}
}

@misc{python_course,
   author = {Bernd Klein},
   title = {Levenstein Distance},
   url = {https://python-course.eu/applications-python/levenshtein-distance.php},
   note = {{Online}, {accessed 20-12-2021}}
}

@book{NLPwP,
    author = {Bird, Steven and Klein, Ewan and Loper, Edward},
    title = {Natural Language Processing with Python},
    year = {2009},
    isbn = {0596516495},
    publisher = {O'Reilly Media, Inc.},
    edition = {1st},
    abstract = {This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and translation. With it, you'll learn how to write Python programs that work with large collections of unstructured text. You'll access richly annotated datasets using a comprehensive range of linguistic data structures, and you'll understand the main algorithms for analyzing the content and structure of written communication. Packed with examples and exercises, Natural Language Processing with Python will help you: Extract information from unstructured text, either to guess the topic or identify "named entities" Analyze linguistic structure in text, including parsing and semantic analysis Access popular linguistic databases, including WordNet and treebanks Integrate techniques drawn from fields as diverse as linguistics and artificial intelligence This book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library. If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages -- or if you're simply curious to have a programmer's perspective on how human language works -- you'll find Natural Language Processing with Python both fascinating and immensely useful.}
}