Sequence labeling method and system, computer equipment and computer readable storage medium

A sequence labeling and sequence technology, applied in the field of sequence labeling methods, systems, computer equipment and computer-readable storage media, can solve problems such as limited linear assumptions and inaccuracy, and achieve the effect of sequence labeling accuracy

Active Publication Date: 2020-03-06
PING AN TECH (SHENZHEN) CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Structural support vector machine sequence labeling has achieved good results, but it is always limited by its own linear assumptions, so it is not accurate enough

Method used

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  • Sequence labeling method and system, computer equipment and computer readable storage medium
  • Sequence labeling method and system, computer equipment and computer readable storage medium
  • Sequence labeling method and system, computer equipment and computer readable storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0053] refer to figure 1 , shows a flow chart of the steps of the sequence labeling method according to Embodiment 1 of the present invention. It can be understood that the flowchart in this method embodiment is not used to limit the sequence of execution steps. An exemplary description is given below taking the computer device 2 as the execution subject. details as follows.

[0054] Step S100, obtaining a training sample set, the training sample set includes a plurality of training sample data, each of the training sample data includes an input text sequence and a label corresponding to the input text sequence.

[0055] Specifically, the training sample set includes multiple input text sequences, each input text sequence corresponds to a training sample data, the input text sequence includes a sentence containing multiple keywords, and the tag corresponding to the sentence is determined according to the part of speech of the keyword, which can be manually Set the label and...

Embodiment 2

[0094]read on Figure 5 , shows a schematic diagram of program modules of Embodiment 2 of the sequence tagging system of the present invention. In this embodiment, the sequence labeling system 20 may include or be divided into one or more program modules, and one or more program modules are stored in a storage medium and executed by one or more processors to complete the present invention. Invention, and can realize the above-mentioned sequence labeling method. The program module referred to in the embodiment of the present invention refers to a series of computer program instruction segments capable of accomplishing specific functions, which is more suitable for describing the execution process of the sequence tagging system 20 in the storage medium than the program itself. The following description will specifically introduce the functions of each program module of the present embodiment:

[0095] The acquiring module 200 is configured to acquire a training sample set, the...

Embodiment 3

[0135] refer to Image 6 , is a schematic diagram of the hardware architecture of the computer device according to Embodiment 3 of the present invention. In this embodiment, the computer device 2 is a device capable of automatically performing numerical calculation and / or information processing according to preset or stored instructions. The computer device 2 may be a rack server, a blade server, a tower server or a cabinet server (including an independent server, or a server cluster composed of multiple servers) and the like. like Image 6 As shown, the computer device 2 at least includes, but is not limited to, a memory 21 , a processor 22 , a network interface 23 , and a sequence labeling system 20 that can communicate with each other through a system bus. in:

[0136] In this embodiment, the memory 21 includes at least one type of computer-readable storage medium, and the readable storage medium includes flash memory, hard disk, multimedia card, card-type memory (for exam...

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Abstract

The embodiment of the invention discloses a sequence labeling method, which comprises the following steps: obtaining a training sample set, wherein the training sample set comprises a plurality of pieces of training sample data, and each piece of training sample data comprises an input text sequence and a label corresponding to the input text sequence; preprocessing each piece of training sample data to obtain vector data corresponding to each piece of training sample data; inputting vector data corresponding to each piece of training sample data into a first-order hidden Markov model to construct a feature vector matched with each piece of training sample data; inputting the feature vectors corresponding to the sample data into a neural network model for training to generate a sequence labeling model; and inputting the to-be-labeled sequence into the sequence labeling model to obtain a target label sequence corresponding to the to-be-labeled sequence. The embodiment of the invention further discloses a sequence labeling system, computer equipment and a readable storage medium. The embodiment of the invention has the beneficial effect that the sequence annotation is more accurate.

Description

technical field [0001] The embodiments of the present invention relate to the technical field of natural speech processing, and in particular to a sequence tagging method, system, computer equipment and computer-readable storage medium. f(x; θ) = argmaxF(x, y; θ) [0002] technical background [0003] At present, sequence tagging is a basic and important problem in natural language processing, which includes tasks such as word segmentation, part-of-speech tagging, named entity recognition, and relationship extraction. The sequence labeling problem is also a classic problem in structure learning, which is achieved by finding to get the label y for the sequence x. [0004] Structural support vector machine is a classic method of structural learning. The goal of structural support vector machine is not only to maximize the score of the correct label sequence, but also to maximize the score between the correct label sequence and the score of the nearest incorrect label sequenc...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/35G06K9/62G06N3/04G06N3/08
CPCG06F16/35G06N3/08G06N3/045G06F18/2411G06F18/214
Inventor 金戈徐亮
Owner PING AN TECH (SHENZHEN) CO LTD
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