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Dimensionality reduction is the mapping of data from a high dimensional space to a lower dimension space such that the result obtained by analyzing the reduced dataset is a good approximation to the result obtained by analyzing the original data set. There are several dimensionality reduction approaches which include Random Projections, Principal Component… (More)

This paper considers two approaches to query-based dimensionality reduction. Given a data set, D, and a query, Q, the first approach performs a random projection on the dimensions of D that are not in Q to obtain the data set D R. A new data set (D RQ) is then formed comprising all the dimensions of D that are in the query Q together with the dimensions of… (More)

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