Adjusted Impact Factor by using F min Search Algorithm

Abstract

Assessing research quality is a crucial task for research institutions. Impact Factor has been widely used as a journal evaluation metric. It also has been used as an evaluation metric for researcher's research ability. However, assessing research quality using Impact Factor can raises various problems, especially when evaluating researchers from different research fields at the same time. For instance, lower Impact Factors are given to traditional engineering and social sciences than those given to general sciences and biology. To solve these problems, adjusted Impact Factor has been proposed. They have the effect of normalizing Impact Factors in different subject categories. However, these revised Impact Factors cause errors in relative rankings among journals. By using linearly combined 11 revised Impact Factor, we find the optimal combination to reduce the error rate and give a solution to weak point of current Impact Factor.