Difference between revisions of "Text summarization"
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Some common approaches to text summarization include the following: | Some common approaches to text summarization include the following: | ||
| − | * | + | * '''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 | ||
== Challenges / Issues == | == Challenges / Issues == | ||
Revision as of 15:54, 30 September 2010
Summary
Text Summarization (also known as summarization, and automatic summarization) is a natural language processing task 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
Some common approaches to text summarization include the following:
- 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
Challenges / Issues
Some major challenges in text summarization
