  In history research, cohort analysis seeks to identify social structures and
figure mobilities by studying the group-based behavior of historical figures.
Prior works mainly employ automatic data mining approaches, lacking effective
visual explanation. In this paper, we present CohortVA, an interactive visual
analytic approach that enables historians to incorporate expertise and insight
into the iterative exploration process. The kernel of CohortVA is a novel
identification model that generates candidate cohorts and constructs cohort
features by means of pre-built knowledge graphs constructed from large-scale
history databases. We propose a set of coordinated views to illustrate
identified cohorts and features coupled with historical events and figure
profiles. Two case studies and interviews with historians demonstrate that
CohortVA can greatly enhance the capabilities of cohort identifications, figure
authentications, and hypothesis generation.
