FEEDBACK-DRIVEN EXOGENOUS FACTOR LEARNING IN TIME SERIES FORECASTING

摘要

A system for forecast modeling includes at least one processor and at least one database that is operably coupled to the at least one processor. The database includes a time series data module that is configured to store time series data for a domain, an exogenous data module that is configured to store exogenous data associated with multiple exogenous factors and a feedback module that is configured to collect and store feedback data from multiple online users, where the feedback data is related to the exogenous data and the exogenous factors. The system includes a data pre-processor module that is configured to use the at least one processor to identify and select a portion of the exogenous factors using the feedback data collected from the online users for use in a forecast model in combination with the time series data for the domain.

主权项

1. A system for forecast modeling, the system comprising:
at least one processor; at least one database that is operably coupled to the at least one processor, wherein the database comprises:
a time series data module that is configured to store time series data for a domain,an exogenous data module that is configured to store exogenous data associated with a plurality of exogenous factors, anda feedback module that is configured to collect and store feedback data from a plurality of online users, wherein the feedback data is related to the exogenous data and the plurality of exogenous factors; and a data pre-processor module that is configured to use the at least one processor to identify and select a portion of the plurality of exogenous factors using the feedback data collected from the online users for use in a forecast model in combination with the time series data for the domain.