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With the wide application of location-predicated gregarious networks (LBSNs), Point of interest guidance has become one of the major accommodations in LBSNs. The deportments of users in LBSNs are mainly checking in Point of Interests, and these checking in deportments are influenced by user's demeanor daily habits and his/her friends. "In convivial networks, convivial influence is often used to avail businesses to magnetize more users". Each user target utilizers have a different influence on different Point of Interest in gregarious networks. This paper culls the list of Point of Interests with the greatest influence for recommending users. Our aims are to gratify the target user's accommodation need, and simultaneously to promote businesses' locations Point of Interests.This Project defines a point of interest guidance quandary for location promotion. Adscititiously, we utilize sub modular properties to solve the optimization quandary. At last, this Project conducted a comprehensive performance evaluation for our method utilizing two authentic LBSN datasets.