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Semantic Mapping (Statistics): Dimensionality Reduction, Clustering, Cluster, Data Set, Data Element, Text Mining, Information Retrieval -

englanti
2026-03-14
146,80 € 195,73 €

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High Quality Content by WIKIPEDIA articles! The semantic mapping (SM) is a dimensionality reduction method that extracts new features by clustering the original features in semantic clusters and combining features mapped in the same cluster to generate an extracted feature. Given a data set, this method construct a projection matrix that can be used to mapping of data elements from one high dimensional spac ... Täydellinen kuvaus

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High Quality Content by WIKIPEDIA articles! The semantic mapping (SM) is a dimensionality reduction method that extracts new features by clustering the original features in semantic clusters and combining features mapped in the same cluster to generate an extracted feature. 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 dimensional space. The SM can be applied in construction of text mining and information retrieval systems, as well as systems managing vectors of high dimensionality. The SM is an alternative to principal components analysis and latent semantic indexing methods.

Lisätietoja

Julkaisija OmniScriptum
Julkaisuvuosi 2026
Kannen tyyppi Pehmeäkantinen
EAN 9786130491451
Kirjoita oma arvostelusi
Arvostelet: Semantic Mapping (Statistics): Dimensionality Reduction, Clustering, Cluster, Data Set, Data Element, Text Mining, Information Retrieval
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146,80 € 195,73 €