Semantic mapping (statistics): Difference between revisions
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The '''Semantic Mapping''' is a [[dimensionality reduction]] method that extract new features by [[clustering]] the original features in semantic clusters and combining those in the same cluter. Given a [[data set]], this method construct a projection matrix that can be used to mapping of [[data element]]s from one high dimensional space into reduced space. The Semantic Mapping can be applied in construction of [[text mining]] and [[information retrieval]] systems, as well as systems managing [[ |
The '''Semantic Mapping''' is a [[dimensionality reduction]] method that extract new features by [[clustering]] the original features in semantic clusters and combining those in the same cluter. Given a [[data set]], this method construct a projection matrix that can be used to mapping of [[data element]]s from one high dimensional space into reduced space. The Semantic Mapping can be applied in construction of [[text mining]] and [[information retrieval]] systems, as well as systems managing [[vector]]s of high dimensionality. |
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Revision as of 22:18, 10 July 2008
The Semantic Mapping is a dimensionality reduction method that extract new features by clustering the original features in semantic clusters and combining those in the same cluter. Given a data set, this method construct a projection matrix that can be used to mapping of data elements from one high dimensional space into reduced space. The Semantic Mapping can be applied in construction of text mining and information retrieval systems, as well as systems managing vectors of high dimensionality.
The Semantic mapping can be also:
- In Semantic Web context - the name of a process done by semantic mappers.
- In Literacy context - the name of the process of generates a semantic map, a graphical model designed to help students identify important ideas and how these ideas fit together in a text.
See also
References
R. F. Correa 21:56, 10 July 2008 (UTC)