occams: A Text Summarization Package

Author:

White Clinton T.1,Molino Neil P.2,Yang Julia S.1,Conroy John M.2ORCID

Affiliation:

1. Department of Defense, USA

2. IDA Center for Computing Sciences, 17100 Science Drive, Bowie, MD 20740, USA

Abstract

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.

Publisher

MDPI AG

Reference29 articles.

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