Long text retrieval model based on comparative learning

The invention provides a long text retrieval model based on comparative learning. The long text retrieval model comprises a legal field pre-training module, a comparative learning module and a retrieval module, wherein the legal field pre-training module is used for constructing a basic long text encoder and performing field pre-training on the long text encoder by using a legal document corpus; the comparative learning module is used for constructing training data from the case annotation data set and performing text vector training on the long text encoder by utilizing the training data, and the training data comprises query statements and positive samples and negative samples of the query statements; and the retrieval module is used for detecting a case corresponding to the long text query statement by adopting the trained long text encoder. By means of the mode, the long text retrieval model can effectively solve the problem that a deep model processes a long text, the document encoder is adjusted by comb