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Econo-ESA is an economic scheme of the explicit semantic analysis (ESA). The scheme properly decreases the ESA index matrix dimensions to achieve faster process with similar results. This paper discusses index matrix dimensional reduction schemes of econo-ESA. We did experiments with several schemes: random selection, k-means clustering, norm-based clustering, densest, and sparsest schemes. Each resulted matrix had different element values and density. Our experimental results showed that the random selection scheme, which had the nearest density to the original index matrix, gave the best results. We thus conclude that the index matrix density is an additional feature which has to be considered in econo-ESA

Econo-ESA Reduction Scheme and the Impact of its Index Matrix Density