Automatic Summarization (Questionnaire 2)

2009/04/25 at 11:08 pm Utzi iruzkina

Automatic summarization is the formation of an abbreviated version of a text, made by a computer program. The main objective of automatic summarization is the following:  first, to take a source of information. After that,  to draw out the contained substance from it and finally, to present the major content to the user in a summarized way. And of course,  in a sensitive way taking into account the users’ needs.

Because of the phenomenon of information overload, we know that the access to  solid and properly-developed summaries is essential. One of the examples we have of the use of summarization technology, is a search engine called Google.

Those technologies have to bear in mind the length, the writing-style and the syntax, in order to make a useful summary of any type of text.

This important technique was born in the 60’s. Nowadays, with both, the Internet and the WWW it has gain a big importance.

Automatic text summarization can be used to do, among other things, the following activities :

  • a) To summarize news to SMS or WAP format for mobile phones/PDA.
  • b) To let a computer synthetical read the summarized text.
  • c) To present shortened search results’ descriptions in search engines


Depending on what the summarization program centers in to make a summary of a text, we can talk about different kind of summaries. For instance generic summaries or query relevant summaries, also known as query-based summaries.

Summarization systems can make query relevant text summaries but also generic machine-generated summaries. This depends on user’s needs. I have to say that summarization of multimedia documents are also possible. In fact, we have examples of some summarizations of pictures and movies.

We can also find systems which based on a single source document, can create a summary. Otherwise, other systems (called multi-document summarization systems) are able to use multiple source documents.



Entry filed under: HLT, Littera. Tags: , , , , .

Information Extraction (Questionnaire 2) Word-Sense Disambiguation (Questionnaire 2)

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