The present application relates to the technical field of
large model, especially to a reading recommendation
large model generation method and
system based on
big data resources.The method comprises the following steps: obtaining a text to be evaluated and collecting reading materials of multiple learning stages and multiple types, labeling them, aggregating and verifying the consistency of the labeling results, and constructing a verified recommendation
database; based on the recommendation
database, performing low-rank adaptive fine-tuning on the general pre-training
large model to obtain
a domain model, and monitoring and correcting the performance and bias during the training process; performing multi-
dimensional analysis on the text to be evaluated to generate a text
feature vector, combining
semantic vector similarity retrieval to perform
hybrid retrieval on the recommendation
database; the present application realizes more accurate and efficient reading recommendation through the construction of the reading recommendation large model.