The invention belongs to the technical field of
big data customer information matching, and discloses an intelligent
customer information matching method based on
big data, which comprises the following steps of: firstly, establishing a scene customer behavior
semantic dictionary according to three groups of new customers, high-value customers and loss early-warning customers, and determining behavior
label mapping rules of different customer types; for example, the browsing duration of a new customer exceeds 3 minutes, the consultation frequency exceeds 2, the behavior is defined as a high-intention behavior, the
semantic dictionary is dynamically updated every 24 hours based on cross-platform semantic conflict feedback, and the cross-platform data semantic standard is unified; secondly, screening weak association features by adopting a
mutual information and customer value double-weight
algorithm, setting weights according to customer value differences, and preferentially retaining features with higher association degree with customer demands to generate structured feature vectors; and finally, deploying a preprocessing effect
verification module at an
edge computing node, performing field secondary labeling, null interpolation
complementation and time format unification operation on the data, and improving the data
standardization level.