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Sequence labelling method and device

A sequence labeling and text sequence technology, applied in special data processing applications, instruments, biological neural network models, etc., can solve the problem of low labeling accuracy and achieve high effectiveness and generalization

Inactive Publication Date: 2018-10-30
UNION MOBILE PAY
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AI Technical Summary

Problems solved by technology

This technical solution avoids cumbersome manual feature extraction and has good generalization ability. However, the existing technical solutions directly use a single neural network or a single model to improve and optimize, resulting in low labeling accuracy, which is comparable to manual labeling results. There is still a lot of room for improvement

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  • Sequence labelling method and device
  • Sequence labelling method and device

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Embodiment Construction

[0034] The application will be described in further detail below in conjunction with the accompanying drawings.

[0035]The sequence tagging method provided by this application can be applied to Chinese Word Segmentation (CWS), Part-of-Speech tagging (POS tagging), Named Entity Recognition (NER), etc. The so-called "sequence labeling" means that for a one-dimensional linear input sequence, for example, the linear input sequence X=x 1 ,x 2 ,x 3 ,...,x i ,...,x n , label each element in the linear sequence with a certain label in the label set, for example, the label set Y=y 1 ,y 2 ,y 3 ,...,y i ,...,y n .

[0036] Therefore, the sequence labeling method is essentially a problem of classifying each element in the linear sequence according to the context content. In general, for Natural Language Processing (NLP) tasks, the linear sequence is the original input text sentence, and a Chinese character or character can often be regarded as an element of the linear sequence,...

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Abstract

The invention discloses a sequence labelling method and device. The method comprises the following steps: a sequence labeling model acquires word vector expression corresponding to each word of an input text sequence through a word vector table; and then the sequence labeling model acquires character vector expression of each character through the character vector table for each character in the text sequence, and splices the character-level feature vector expression of the word and the word vector expression for each word, thereby obtaining the spliced word vector expression of the word; andfinally, the sequence labeling model performs sequence labeling processing on the spliced word vector expression of each word of the text sequence to obtain to a label sequence of the text sequence. The method is used for providing the sequence labeling model with high generalization and accuracy.

Description

technical field [0001] The invention relates to the field of artificial intelligence, in particular to a sequence labeling method and device. Background technique [0002] With the rapid development of emerging media such as the Internet in recent years, human beings have entered the era of information explosion. At the same time, it is increasingly hoped that computers can understand human language to better help humans complete various daily tasks. Therefore, natural language processing has become a research hotspot in recent years. In natural language processing, the sequence annotation model is the most common model, and it is also widely used. Different from general classification problems, the sequence labeling model outputs a label sequence. Generally speaking, tags are related to each other and constitute the structural information between tags. Using these structural information, the sequence labeling model can often achieve higher performance than traditional c...

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Application Information

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IPC IPC(8): G06F17/27G06N3/04
CPCG06F40/289G06N3/045
Inventor 刘壮张文凌闫成
Owner UNION MOBILE PAY
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