Text summarization

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Text Summarization (also known as summarization, and automatic summarization) is a natural language processing problem which focuses on creating shortened versions of texts with computer algorithms/software that retain the important points of the original piece of text.

Common Approaches

Common approaches to text summarization can typically be classified into one of the following categories:

  • Extraction, extracts most important information (sentences or paragraphs) from original text and copies them to make summary
  • Abstraction, paraphrases sections in the original text and relies on language generation to make the summaries coherent


One commonly used evaluation metric in summarization is ROUGE, which is used in NIST's Document Understanding Conferences' summarization tasks. It is considered as an Automatic Evaluation Method.

Example Systems

References / Links

  • A bit outdated website with some references related to text summarization - [1]
  • Wikipedia article on automatic summarization - [2]

Relevant Papers