An Applied Study of English Sentence Fast Retrieval Algorithm Based on Choquet Expectation

In this paper, the basic structure of fuzzy integral-based multi-classifier fusion model is used as a reference to construct Choquet integral vectors, measure the similarity of English sentences, and construct a fast retrieval algorithm for English sentences based on Choquet expectation.Determine the algorithm threshold and compare the running time of similar retrieval algorithms.Deploy the algorithm into the English sentence retrieval model for dataset training and comparison experiments.Verify the model robustness and determine the chosen K value for the model.Further use the test set to compare the retrieval effectiveness of the model with the traditional semantic retrieval model.The algorithm threshold is set to 6 to improve English sentence recall.The running time consumption of the algorithm is 0.827s and 1.941s, which is lower than the other three similar retrieval algorithms.In the dataset comparison experiments, the algorithmic model of this paper scores better than the comparison model in all 5 evaluation metrics.The model has the best robustness when k takes the value of 15.The model check accuracy and check completeness are higher than the semantic retrieval model LM by nearly 8 percentage points.The fast retrieval algorithm for English sentences based on Choquet expectation can improve sentence retrieval timeliness and retrieval accuracy, and reduce retrieval energy consumption.