Abstract: A numerical generalization method for machine translation and system, computer and computer program thereof includes a training stage, in the training stage, a training corpus is processed in a special manner, and a normal training is performed without changing a structure of a neural network model; and a translation stage, in the translation stage, a generalization label in a translation is replaced with a normal translation. In the present invention, only the pre-processing and post-processing are changed to make the generalization technology applicable, which expands the application of the generalization technology in a neural network machine translation, and better adapts to the new machine translation model structure.

Abstract: A Korean named entity recognition method based on a maximum entropy model and a neural network model, which includes: building a prefix tree dictionary, wherein when a template for any combined noun or a template of any proper noun is matched with an input sentence, the combined noun or proper noun is recognized as a target word; obtaining the target word from a target word selection module and searching for the target word in an entity dictionary, wherein when only one subcategory is matched, the subcategory is used as a tag for the target word; using the maximum entropy model and multiple kinds of linguistic information; constructing a feed-forward neural network mode; and combining adjacent words into an entity tag according to a template selection rule.

Abstract: A numerical generalization method for machine translation and system, computer and computer program thereof includes a training stage, in the training stage, a training corpus is processed in a special manner, and a normal training is performed without changing a structure of a neural network model; and a translation stage, in the translation stage, a generalization label in a translation is replaced with a normal translation. In the present invention, only the pre-processing and post-processing are changed to make the generalization technology applicable, which expands the application of the generalization technology in a neural network machine translation, and better adapts to the new machine translation model structure.