Text Summarization Algorithm

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A text summarization algorithm is an NLP algorithm that can solve a text summarization task.



References

2014

  • (Wikipedia, 2014) ⇒ http://en.wikipedia.org/wiki/Automatic_summarization Retrieved:2014-9-10.
    • ... Generally, there are two approaches to automatic summarization: extraction and abstraction. Extractive methods work by selecting a subset of existing words, phrases, or sentences in the original text to form the summary. In contrast, abstractive methods build an internal semantic representation and then use natural language generation techniques to create a summary that is closer to what a human might generate. Such a summary might contain words not explicitly present in the original. Research into abstractive methods is an increasingly important and active research area, however due to complexity constraints, research to date has focused primarily on extractive methods.

2007

2002

2001

1999

1997

1982

  • (DeJong, 1982) ⇒ G. F. DeJong. (1982). "An overview of the FRUMP system." In: Strategies for Natural Language Processing, W.G.Lehnert & M.H.Ringle (Eds).
    • Domain specific
    • Skimmed and summarised news articles.
    • Template instantiation system
    • Identified which articles belonged to a particular domain.