The invention relates to the technical field of
artificial intelligence, and particularly discloses an
artificial intelligence-based automatic identification method and
system for fraud-related numbers, which breaks through the limitation that a traditional method depends on single-dimensional data through a
data acquisition module, comprehensively describes a number behavior mode through multi-
source data fusion, reduces erroneous judgment and missed judgment caused by one-sided data, and improves the identification accuracy of fraud-related numbers. A data foundation is laid for accurate identification; the feature
library construction module introduces a
knowledge graph technology, constructs the number, the associated object and the behavior event into a graph, and combines data cleaning and
feature extraction and screening to form a dynamically updated fraud-related feature
library; the method not only captures the surface behavior characteristics of the number, such as the
call duration and the short message content, but also can mine the hidden fraud relation network to update the novel fraud characteristics in time, thereby solving the problem that the traditional method lags in the recognition of the complex fraud mode, and improving the timeliness and depth of the feature
library.