The invention discloses an accurate
analysis method for Internet user behaviors based on
artificial intelligence, and the method belongs to the technical field of Internet, and comprises the steps: collecting user behaviors and basic attribute information through a multi-
source data collection technology, and integrating data through a data fusion
algorithm after data cleaning and preprocessing; designing and extracting a plurality of behavior features, screening key features by using a
feature selection algorithm, and performing
feature transformation processing at the same time; constructing a
deep learning model fusing a
recurrent neural network (such as LSTM and GRU), a
convolutional neural network and the like, training the model by using a large-scale
data set, and optimizing parameters; establishing a real-time analysis
system, inputting new data into the model in real time, providing personalized service and recommendation according to an analysis result, and collecting feedback data to update the model online; and finally, evaluating the model by adopting multiple evaluation indexes, verifying the generalization ability through methods such as
cross validation and the like, and further optimizing and adjusting the model.