This invention discloses a method and
system for intelligent matching of preferred products based on user profiles, specifically relating to the field of e-commerce
data processing technology. The method includes obtaining user account rights transaction records, filtering transaction lines based on
payment completion markers, using the receiving field as the object
primary key, forming an occupancy interval based on the start and end times of rights, and attaching the redemption time and purchase price to output a successful purchase table; merging the successful purchase tables by object
primary key and forming an observation sequence based on
transaction time, forming a preference
continuation factor based on the
primary key, a demand occupancy factor based on the intersection of intervals, and a price
response factor based on the
price difference following the purchase result, outputting a
factor graph; extracting the object primary key, occupancy interval, purchase price, and redemption feedback from successful transaction records, constructing a
factor graph, and separating the preference retention state and demand
extinction state using a factor
hidden Markov model algorithm, and then generating a purchase suppression set and a purchase strategy sequence using a particle learning
algorithm and a strategy price determination process.