Alibaba Group Holding Limited

Hu Wei

Chen Zhu

Xu Qiang Yue

Jing Feng Luo

Ling Cao

Zhongyi Liu

Chao Yang

Na Ni

Junwu Xiong

Disclosed is a recommendation method and device. The recommendation method and device includes: acquiring current user behavior data in a currently operating network system in real time to obtain real-time user behavior data of users on the network, the current user behavior data representing currently occurring user rating activities of the users on the network; updating existing rating data of the users, the existing rating data representing user ratings of network objects made by the users during prior interactions with the network system or other network systems, the updating comprising modifying the user ratings in accordance with the real-time acquired user behavior data to obtain current user rating data of the users currently interacting with the network system; determining based upon the current user rating data, one or more similarities chosen from a group of similarities consisting of similarities between the users on the network, similarities between the network objects rated by the users, and between similarities between the users and the network objects; and sending to users recommendations for new recommended network objects to users according to one or more of the determined similarities, the recommendations being sent to users while the users are currently interacting with the network system. The present disclosure can increase recommendation precision and improve recommendation effect.

Recommendation method and device

Disclosed is a recommendation method and apparatus. The recommendation method comprises: identifying at least one core user of a network service provider and a set of users who have demonstrated one or more network-related behaviors with respect to a first predetermined association item; sampling the set of users to identify a set of sample users; calculating a similarity between the sample users to identify a list of similar users; and sending a recommendation of potential users to a network service provider, the recommendation of potential users based on the list of similar users and the at least one core user of a network service provider. Potential users may be efficiently recommended to a network service provider.

Recommendation method and apparatus

Saving database storage space includes receiving, using a processor, one or more properties associated with a newly released commodity input at a front-end server; determining whether the one or more properties of the newly released commodity match a standard property unit (SPU), wherein the SPU includes a plurality of properties common to at least two commodities of which data is stored at a back-end server; and in the event that the one or more properties of the newly released commodity match the SPU, storing data associated with binding the newly released commodity with the matching SPU at the back-end server.

Method and system for processing product properties

Method and system for saving database storage space

Saving database storage space includes extracting a standard property unit from a database of commodity information and including the SPU in a SPU library, generating a sequence document of the standard property unit and sending the sequence document to a front-end device, determining whether a newly released commodity matches the standard property unit of the sequence document of the standard property unit and in the event that the newly released commodity matches the standard property unit of the sequence document, binding the new released commodity and the matched standard property unit.

Growing community of inventors

Hangzhou, China

Hu Wei