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Chinese word vector modeling method
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A modeling method and word vector technology, applied in the field of vector modeling, can solve problems such as low intelligence, inconvenient use, and unregistered word representation, and achieve the effects of high intelligence, improved accuracy, and convenient use
Inactive Publication Date: 2020-08-14
WEIFANG UNIV OF SCI & TECH
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[0005] A Chinese word vector modeling method proposed by the present invention solves the problem that the existing Chinese word vector modeling methods simply introduce information such as radicals and strokes, and at the same time cannot reasonably represent unregistered words, and cannot automatically update sentences. It is not up to the trend of the times, and the degree of intelligence is low, which leads to the problem of inconvenient use
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Embodiment 1
[0034] refer to figure 1 , a Chinese word vector modeling method, comprising the following steps:
[0035] S1: Obtain the corpus base of Chinese words and sounds, and classify them, and at the same time, classify the types with A-type numbers;
[0036] S2: Number the corpus bases in each type sequentially in B category;
[0037] S3: Map the number into the vector space;
[0038] S4: Build a basic model based on the corpus;
[0039] S5: Input Chinese words, detect the sentence length, and detect the corpus basis in Chinese words;
[0040] S6: convert the detected corpus into numbers, and judge the conversion result;
[0041] S7: Map the number to a real number vector in the vector space;
[0042] S8: Carry out word segmentation processing on the corpus basis of Chinese words, and detect the results;
[0043] S9: Input word segmentation processing results into the basic model;
[0044] S10: Complete Chinese word vector modeling.
[0045] In the present embodiment, in sai...
Embodiment 2
[0048] refer to figure 1 , a Chinese word vector modeling method, comprising the following steps:
[0049] S1: Obtain the corpus base of Chinese words and sounds, and classify them, and at the same time, classify the types with A-type numbers;
[0050] S2: Number the corpus bases in each type sequentially in B category;
[0051] S3: Map the number into the vector space;
[0052] S4: Build a basic model based on the corpus;
[0053] S5: Input Chinese words, detect the sentence length, and detect the corpus basis in Chinese words;
[0054] S6: convert the detected corpus into numbers, and judge the conversion result;
[0055] S7: Map the number to a real number vector in the vector space;
[0056] S8: Carry out word segmentation processing on the corpus basis of Chinese words, and detect the results;
[0057] S9: Input word segmentation processing results into the basic model;
[0058] S10: Complete Chinese word vector modeling.
[0059] In the present embodiment, in the...
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Abstract
The invention belongs to the field of vector modeling, and particularly relates to a Chinese word vector modeling method. According to an existing Chinese word vector modeling method, only radical strokes and other information are simply introduced, and meanwhile unregistered words cannot be reasonably expressed. In order to solve the problems of inconvenience in use due to incapability of automatically updating statements, incapability of following the trend of the times and low intelligent degree in the prior art, the invention provides the following scheme that the method comprises the following steps: S1, obtaining corpus bases of form and sound characteristics of Chinese words, classifying the corpus bases, and carrying out A-type numbering on the types of the corpus bases; S2, sequentially carrying out B-type numbering on the corpus foundation in each type; and S3, mapping the number to a vector space. The unregistered words can be reasonably expressed, statements can be automatically updated, the trend of the times can be followed, the intelligent degree is high, and use is convenient.
Description
technical field [0001] The invention relates to the technical field of vector modeling, in particular to a Chinese word vector modeling method. Background technique [0002] Word embeddings have become an essential part of any deep learning-based natural languageprocessingsystem. Natural languageprocessing systems encode words and sentences in fixed-length dense vectors, resulting in vastly improved processing of text data by neural networks. [0003] The existing Chinese word vector modeling methods simply introduce information such as radicals and strokes, and at the same time cannot reasonably represent unregistered words, cannot automatically update sentences, cannot keep up with the trend of the times, and have a low degree of intelligence, resulting in inconvenient use. [0004] Therefore, we propose a Chinese word vector modeling method to solve the above problems. Contents of the invention [0005] A Chinese word vector modeling method proposed by the present ...
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