  This paper investigates the information geometrical structure of a
determinantal point process (DPP). It demonstrates that a DPP is embedded in
the exponential family of log-linear models. The extent of deviation from an
exponential family is analyzed using the $\mathrm{e}$-embedding curvature
tensor, which identifies partially flat parameters of a DPP. On the basis of
this embedding structure, the duality related to a marginal kernel and an
$L$-ensemble kernel is discovered.
