  In this article we show how power transformations can be used as a common
framework for the derivation of local term weights. We found that under some
parametric conditions, BM25 and inverse regression produce equivalent results.
As a special case of inverse regression, we show that the largest increment in
term weight occurs when a term is mentioned for the second time. A model based
on inverse regression (BM25IR) is presented. Simulations suggest that BM25IR
works fairly well for different BM25 parametric conditions and document
lengths.
