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In this article we show how power transformations can be used as a commonframework for the derivation of local term weights. We found that under someparametric conditions, BM25 and inverse regression produce equivalent results.As a special case of inverse regression, we show that the largest increment interm weight occurs when a term is mentioned for the second time. A model basedon inverse regression (BM25IR) is presented. Simulations suggest that BM25IRworks fairly well for different BM25 parametric conditions and documentlengths.

Local Term Weight Models from Power Transformations: Development of BM25IR: A Best Match Model based on Inverse Regression