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Cross-Lingual Text Mining

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Encyclopedia of Machine Learning

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Definition

Cross-lingual text mining is a general category denoting tasks and methods for accessing the information in sets of documents written in several languages, or whenever the language used to express an information need is different from the language of the documents. A distinguishing feature of cross-lingual text mining is the necessity to overcome some language translation barrier.

Motivation and Background

Advances in mass storage and network connectivity make enormous amounts of information easily accessible to an increasingly large fraction of the world population. Such information is mostly encoded in the form of running text which, in most cases, is written in a language different from the native language of the user. This state of affairs creates many situations in which the main barrier to the fulfillment of an information need is not technological but linguistic. For example, in some cases the user has some knowledge of the language in which the text containing a...

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Recommended Reading

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Author information

Authors and Affiliations

    Authors
    1. Nicola Cancedda
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    2. Jean-Michel Renders
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    Editor information

    Editors and Affiliations

    1. School of Computer Science and Engineering, University of New South Wales, Sydney, Australia, 2052

      Claude Sammut

    2. Faculty of Information Technology, Clayton School of Information Technology, Monash University, P.O. Box 63, Victoria, Australia, 3800

      Geoffrey I. Webb

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    © 2011 Springer Science+Business Media, LLC

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    Cancedda, N., Renders, JM. (2011). Cross-Lingual Text Mining. In: Sammut, C., Webb, G.I. (eds) Encyclopedia of Machine Learning. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-30164-8_189

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