发明名称 TIME SERIES TECHNIQUE FOR ANALYZING PERFORMANCE IN AN ONLINE PROFESSIONAL NETWORK
摘要 The disclosed embodiments relate to a system for analyzing performance in an online professional network. During operation, the system receives time series data for user actions, wherein for each user action, the time series data comprises a series of numbers associated with consecutive time intervals, wherein a given number indicates a number of times the user action occurred during the time interval. The system also receives time series data for performance metrics, wherein for each performance metric, the time series data comprises a series of numbers associated with consecutive time intervals, wherein a given number indicates the number of times the performance metric occurred during the time interval. The system then performs a time series analysis on the received time series data for user actions and performance metrics to determine relationships between the user actions and the performance metrics.
申请公布号 US2014358644(A1) 申请公布日期 2014.12.04
申请号 US201414151517 申请日期 2014.01.09
申请人 Linkedin Corporation 发明人 Anand Sathyanarayan;Chen Guangde;Fu Xin
分类号 G06Q10/06 主分类号 G06Q10/06
代理机构 代理人
主权项 1. A computer-implemented method for analyzing performance in an online professional network, the method comprising: receiving time series data for user actions, wherein for each user action, the time series data comprises a series of numbers associated with consecutive time intervals, wherein a given number indicates a number of times the user action occurred during the time interval; receiving time series data for performance metrics, wherein for each performance metric, the time series data comprises a series of numbers associated with consecutive time intervals, wherein a given number indicates the number of times the performance metric occurred during the time interval; and using the received time series data for user actions and performance metrics to construct a time series model, which comprises a regular time series model, and also a seasonal time series model to handle seasonal patterns in the time series data; and solving the time series model using a multivariate regression technique.
地址 Mountain View CA US