occams: A Text Summarization Package

Clinton T. White, Neil P. Molino, Julia S. Yang, John M. Conroy
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引用次数: 1

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.
occams:文本摘要包
提取文本摘要从文档中选择句子的一小部分,这可以很好地“覆盖”文档。当给定一组表示术语重要性的术语权重时,覆盖率的概念可以形式化为称为预算最大覆盖率问题的组合优化问题。这类的提取方法被认为是最好的经典提取摘要系统之一。本文简要介绍了occams软件包,它是一个基于算法的多语言提取单文档和多文档摘要软件包,该算法给出了预算最大覆盖问题的最优逼近。occams包是用Python编写的,并提供了一个易于使用的模块化接口,允许它与流行的Python NLP包(如nltk, stanza或space)一起工作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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