A Corpus Processing and Analysis Pipeline for Quickref

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Abstract

Quicklisp is a library manager working with your existing Common Lisp implementation to download and install around 2000 libraries, from a central archive. Quickref, an application itself written in Common Lisp, generatesautomatically and by introspection, a technical documentation for every library in Quicklisp, and produces a website for this documentation. In this paper, we present a corpus processing and analysis pipeline for Quickref. This pipeline consists of a set of natural language processing blocks allowing us to analyze Quicklisp libraries, based on natural language contents sources such as README filesdocstrings, or symbol names. The ultimate purpose of this pipeline is the generation of a keyword index for Quickrefalthough other applications such as word clouds or topic analysis are also envisioned.


Bibtex (lrde.bib)

@InProceedings{	  hacquard.21.els,
  author	= {Antoine Hacquard and Didier Verna},
  title		= {A Corpus Processing and Analysis Pipeline for Quickref},
  booktitle	= {14th European Lisp Symposium},
  year		= 2021,
  pages		= {27--35},
  month		= may,
  address	= {Online},
  isbn		= 9782955747452,
  doi		= {10.5281/zenodo.4714443},
  abstract	= {Quicklisp is a library manager working with your existing
		  Common Lisp implementation to download and install around
		  2000 libraries, from a central archive. Quickref, an
		  application itself written in Common Lisp, generates,
		  automatically and by introspection, a technical
		  documentation for every library in Quicklisp, and produces
		  a website for this documentation. In this paper, we present
		  a corpus processing and analysis pipeline for Quickref.
		  This pipeline consists of a set of natural language
		  processing blocks allowing us to analyze Quicklisp
		  libraries, based on natural language contents sources such
		  as README files, docstrings, or symbol names. The ultimate
		  purpose of this pipeline is the generation of a keyword
		  index for Quickref, although other applications such as
		  word clouds or topic analysis are also envisioned.}
}