Analytics (Jun 2023)

<tt>occams</tt>: A Text Summarization Package

  • Clinton T. White,
  • Neil P. Molino,
  • Julia S. Yang,
  • John M. Conroy

DOI
https://doi.org/10.3390/analytics2030030
Journal volume & issue
Vol. 2, no. 3
pp. 546 – 559

Abstract

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Extractive text summarization selects asmall subset of sentences from a document, which gives good “coverage” of a document. When given a set of term weights indicating the importance of the terms, the concept of coverage may be formalized into a combinatorial optimization problem known as the budgeted maximum coverage problem. Extractive methods in this class are known to beamong the best of classic extractive summarization systems. This paper gives a synopsis of thesoftware package occams, which is a multilingual extractive single and multi-document summarization package based on an algorithm giving an optimal approximation to the budgeted maximum coverage problem. The occams package is written in Python and provides an easy-to-use modular interface, allowing it to work in conjunction with popular Python NLP packages, such as nltk, stanza or spacy.

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