Interest is rising for alterative impact measures derived from Garfield's Journal Impact Factor (JIF). Those new measures cope with the diversity of scientific practices across areas and/or with chains of knowledge circulation. In additional to classical ex-post normalization based on statistical standardization field by field, mostly on the basis of predefined fields such as Thomson Reuter's "subject categories", two alternative families of measures have appeared. The first family builds on the classical "journal influence weight" of Pinski &Narin (1976), one of the forerunners of Google algorithms which in turn triggered new approaches of influence chains. The principle is to weight iteratively emitted citations by the impact of the source. Bergström's Journal Eigenfactor (2007) based on Thomson data, challenged by Scimago (de Moya-Anegon) based on Scopus are the best known examples. Depending on the settings, those measures can address two issues simultaneously, the variability of citing practices across areas and the chains of prestige. The second family, citing-side normalization, appeared recently with the Audience factor (Zitt & Small, 2008; Zitt, 2010) and then the SNIP (Moed, 2009-2010). They only aim only at correcting the measures of impact for the variability of citing practices typically with a choice of classification-free measure.