| With the rapid development of the Internet,each user generates a large amount of data and spreads through the Internet.Thus,the amount of data is exploding.Behind the massive data contains a variety of user information.By mining user data and constructing user profile to reflect user characteristics and preferences,product providers can bring better personalized services to users,increase user stickiness and increase product value.This paper starts from the requirement of user profile products and implements a user profile system for Internet products by means of big data technology.The system supports data collection from diverse sources and different data sources.Using distributed computing to achieve terabytes of data volume processing.The system supports both offline and real-time calculations,and can handle massive data while taking into account timeliness.At the level of tag value calculation,this paper innovatively proposes to generate tag values through page configuration and user segmentation through page screening.This allows product and operation teams to create tags and divide user groups on demand to enable data analysis for selected users,eliminating the need for data analysts to develop new reports for specific people each time.With the help of the search engine,the system achieves billion-level user volume query seconds return,which greatly reduces the time cost for users to query large amounts of data.At present,the system has been officially launched,serving the product,operation,push,recommendation and other teams through page query,interface call,data push,which has produced practical value for the business side.This paper introduces in detail the process of user profile system from design to implementation in the industry,hoping to provide reference value for relevant practitioners to build similar systems. |
