Automatic summarization: Difference between revisions

Revision as of 07:48, 20 September 2004

Revision as of 07:50, 20 September 2004

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Nowadays, summarization systems are able to create both query relevant text summaries or generic machine-generated summaries depending on what the user needs. Summarization of multimedia documents, e.g. pictures or movies are also possible.

Machine learning techniques from closely related fields such as [[Information Retrieval]] or [[Text Miningmining]] have been successfully adapted to help automatic summarization.

Apart from fully automated summarizers (FAS) there are systems that aid humans with the task of summarization (MAHS = machine aided human summarization), for example by highlighting candidate passages to be included in the summary, and there are systems that depend on post-processing by a human (HAMS = human aided machine translation).