1. A method of generating recommended items for a current user in an unfamiliar domain, comprising: selecting a reference user in a reference domain different from the unfamiliar domain, wherein current user behavior in the reference domain and reference user behavior in the reference domain have a user similarity index which satisfies a user similarity index condition; and generating the recommended items in the unfamiliar domain for the current user according to history behavior data of the reference user in the unfamiliar domain.