Research on civil aircraft verification test data retrieval technology based on word segmentation

There is a massive amount of unstructured data in cıvıl aircraft validation tests, which is difficult to conduct data retrieval and application based on file content. The traditional segmentation retrieval methods cannot meet the segmentation retrieval requirements in the field of validation tests. A segmentation retrieval method based on statistics and terminology dictionaries for the field of validation experiments is proposed. Firstly, the conditional ran-dom fields (CRF) model is used to achieve text initial segmentation. Then, based on the domain files, a terminolo-gy dictionary is constructed, and combined with the reverse maximum matching (RMM) algorithm on the basis of the terminology dictionary and the initial segmented text to achieve professional segmentation of the text. Finally, based on the professional segmentation results, the unstructured files are divided and indexed to support data re-trieval based on file content. A case segmentation is conducted using the text content of a certain experimental outline, and compared with traditional statistical segmentation methods such as CRF, N-gram, and hidden Markov model (HMM). The results show that the proposed method exhibited the best accuracy in professional segmentation, and can build a civil aircraft validation test database and achieve rapid retrieval of unstructured files in the database.