In recent years, Evolutionary clustering is an evolving rese arch area in data mining. The evolution diagnosis of any homogeneous as well as heterogeneous network will provide an overall view about the network. Applications of evolutionary clustering includes, analyzing, the social networks, information networks, about their structure, properties and behaviors. In this paper, the authors study the problem of influence of priors over multi-typed object in evolutionary clustering. Priors are defined for each type of object in a heterogeneous information network and experimental results were produced to show how consistency and quality of cluster changes according to the priors.