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Entity normalization method and device

A normalization and entity technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve problems affecting the accuracy of normalization

Inactive Publication Date: 2020-01-10
BEIJING GRIDSUM TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, since machine learning is heavily dependent on training data, in actual application scenarios, manual annotation is required, which will affect the accuracy of normalization

Method used

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  • Entity normalization method and device
  • Entity normalization method and device
  • Entity normalization method and device

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Embodiment Construction

[0040] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided for more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0041] An embodiment of the present invention provides a method for entity normalization. The method flow chart of the method is as follows figure 1 shown, including the following steps:

[0042] S10, analyzing the entity to be normalized in a preset analysis manner to obtain a search field;

[0043] In this implementation, the preset analysis method may be any one or more of word segmentation, pinyinization and word segmentation....

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Abstract

The invention discloses an entity normalization method and device. The method comprises the steps of analyzing a to-be-normalized entity in a preset analysis mode to obtain a retrieval field; comparing the retrieval field with each corpus field in a corpus by utilizing a corpus matching model to obtain the similarity between the retrieval field and each corpus field; and determining a standard entity corresponding to the to-be-normalized entity based on the similarity between the retrieval field and each corpus field. Based on the method, the relevancy between the to-be-normalized entity and each standard entity in the preset industry standard dictionary can be measured in a preset analysis mode, so that an entity normalization task is completed. Manual intervention is not needed, an unsupervised mode is adopted, a training set related to the field does not need to be prepared, precision is high, and the method is suitable for most entity normalization tasks.

Description

technical field [0001] The invention relates to the field of natural language processing, in particular to a method and device for entity normalization. Background technique [0002] Entity normalization, also known as entity disambiguation, is one of the common tasks in the field of natural language processing. Its task is to map non-standard entities from the text to standard entities. [0003] At present, entity normalization mainly relies on machine learning, that is, using machine learning algorithms to learn the correlation between entities to be normalized and standard entities from the training set, so as to transform the normalization task into a sorting task. However, since machine learning relies heavily on training data, manual annotation is required in practical application scenarios, which will affect the accuracy of normalization. Contents of the invention [0004] In view of the above problems, the present invention is proposed to provide an entity normal...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/332
Inventor 张广鹏
Owner BEIJING GRIDSUM TECH CO LTD