A study on the classification of stylistic and formal features in English based on corpus data testing

ABSTRACT: The traditional statistical and rule combination algorithm lacks the determination of the inner cohesion of words, and the N-gram algorithm does not limit the length of N, which will produce a large number of invalid word strings, consume time and reduce the efficiency of the experiment. Therefore, this article first constructs a Chinese neologism corpus, adopts improved multi-PMI, and sets a double threshold to filter new words. Branch entropy is used to calculate the probabilities between words. Finally, the N-gram algorithm is used to segment the preprocessed corpus. We use multi-word mutual information and a double mutual information threshold to identify new words and improve their recognition accuracy. Experimental results show that the algorithm proposed in this article has been imp

SUBMITTER: Li S 

PROVIDER: S-EPMC10280581 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature