Word vector training method and system fusing word class information and position information

Abstract

The invention discloses a word vector training method and system fusing word class information and position information. The method includes the steps that data is preprocessed to obtain a target text; the target text is subjected to word segmentation and word class tagging; the word class information and the position information are modeled; the word class information and the position information are fused on the basis of a skip-gram model based on the negative sampling strategy for word vector learning to obtain target word vectors, and the target word vectors are used for word analog task and word similarity task evaluation. The word class information and the position information of words are considered, on the basis of modeling the word class information and the position information of the words, the word class information of the words and the position information between word classes are fully used for helping training of the word vectors, and parameters are updated more reasonably in the training process.

Description

technical field [0001] The invention belongs to the technical field of natural language processing, and more specifically relates to a word vector training method and system that integrates part of speech and position information. Background technique [0002] In recent years, with the rapid development of mobile Internet technology, the scale of data in the Internet has grown rapidly, and the complexity of data has also increased dramatically. This makes the processing and analysis of these massive unstructured and unlabeled data a major problem. [0003] Traditional machine learning methods use feature engineering (Feature engineering) to symbolize data to facilitate model modeling and solution. However, bag-of-words representation techniques commonly used in feature engineering, such as One-hot vectors, increase with the complexity of data. The dimensionality of features will also increase dramatically leading to the curse of dimensionality problem. And there is still a...

AI Technical Summary

Problems solved by technology

[0005] In view of the above defects or improvement needs of the prior art, the object of the present invention is to provide a word vector training method and system that fuses part-of-speech and position information, thereby solving the problem of part-of-speech in the research work of fusion of part-of-speech information in the prior art. The granularity is relatively large, the use of part-of-speech information is insufficient, and the update of part-of-speech information is not reasonable.

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