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'''Automatic Summarization''' is the creation of a [[short]]ened version of a [[text]] by a [[computer program]]. The product of this procedure still contains the most important points of the original text.
Access to [[coherent]] and correctly-developed text summaries can be of great use, especially in our time of [[information overload]], in which the amount of information electronically available to us, grows every day. A good example of the use of summarization technology could be [[search engine]]s such as [[Google]].
[[Technology|Technologies]] that can make a [[coherent]] summary, of any kind of text, need to take into account several [[variable]]s such as length, writing-style and [[syntax]] to make a useful summary.
==Extraction and abstraction==
Broadly, one distinguishes two approaches: ''[[extraction]]'' and ''[[abstraction]]''.
Extraction techniques merely copy the information deemed most important by the system to the summary, while abstraction involves paraphrasing sections of the [[source document]]. In general, abstraction can condense a text more strongly than extraction, but the programs that can do this are harder to program.
==Types of summaries==
There are different types of summaries depending what the summarization program focuses on to make the summary of the text, for example ''[[sentence extraction]] summaries'', ''generic summaries'' or ''query relevant summaries''.
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.
==Aided summarization==
Machine learning techniques from closely related fields such as [[Information Retrieval]] or [[Text mining]] have been successfully adapted to help automatic summarization.
Apart from Fully Automated Summarizers (FAS), there are systems that aid users 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 Summarization).
== Further Reading ==
Endres-Niggemeyer, Brigitte (1998): Summarizing Information (ISBN 3540637354)
Mani, Inderjeet (2001): Automatic Summarization (ISBN 1588110605)
==External link==
[http://www.acm.org/sigir/ http://www.acm.org/sigir/]
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