Computer scienceData scienceNLPMain NLP tasksText summarization

Overview of text summarization

Theory

Classical extractive summarization overview

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Match the approaches to their short descriptions:

Match the items from left and right columns
Machine learning approaches
Frequency-driven approaches
Graph methods
Tackles summarization as a binary classification problem. There is a training set of document-extractive summary pairs
The weights of words are binary or continuous, and the weights show the word's correlation to the topic
Sentences are represented as the vertices and edges indicate the sentence similarity
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