Adaptive Retrieval Method of Legal Information based on Artificial Intelligence

In the current legal information retrieval methods, keywords are used for extraction and neural networks are used for search. However, the keywords of cases in legal information are different. Simply using keywords to extract the search results in insufficient accuracy. Therefore, an adaptive retrieval method of legal information based on artificial intelligence is proposed. First, establish a positional legal language model to determine the total number of spreads in the term. According to the definition of the term in the model, calculate the similarity of the semantic concept of the term. After confirming that the concept is similar to the term, calculate the co-occurring words in the term. Finally, an artificial intelligence algorithm is used to retrieve the co-occurring words. In order to verify the feasibility of the designed retrieval method, literature [1], literature [2] and design methods were used to retrieve the contents of a certain legal information database. The experimental results show that the designed retrieval method has a higher retrieval accuracy and meets the design requirements.