Depending on the type of information network, network embedding is classified into homogeneous and heterogeneous (HIN) embedding. Compared with HIN composition more complex contains richer semantics. At present, research relatively mature. However, if model directly applied to HIN, it will cause incomplete extraction. It necessary build a specialized for HIN. Learning based meta-path an effecti...

In this paper, the existing scenic spot recommendation algorithms ignore implicit trust and transmission of users when dealing with user relationships, lack historical browsing behavior data in new city scenes leads to an inaccurate recommendation. a personalized method combining relationship tag preference is proposed. Firstly, degree introduced quality poor only considering similarity users. ...