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Text labeling method and system

A technology of text and text data, which is applied in the direction of text database query, unstructured text data retrieval, natural language data processing, etc. It can solve the problem of inability to effectively mark attribute labels, inability to form pipeline operations, and inability to simplify user operations and information filtering processes and other issues, to achieve the effect of simplifying the operation and information filtering process, improving work efficiency, and efficient labeling

Pending Publication Date: 2020-05-08
深圳数阔信息技术有限公司
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  • Description
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  • Application Information

AI Technical Summary

Problems solved by technology

[0006] In the existing technology, it is impossible to effectively mark all the attribute labels and their emotions in the text to form a standardized corpus; when marking, the user's operation and information filtering process cannot be simplified, and in the process of inputting text into the generation model, it is impossible to form Pipeline operation, improve overall work efficiency

Method used

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  • Text labeling method and system

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Experimental program
Comparison scheme
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Embodiment

[0054] like image 3 As shown, the text labeling method provided by the embodiment of the present invention includes:

[0055] S01: Filter out valid text data according to text filtering rules.

[0056] After the data is imported, filtering and cleaning are performed first to filter out valid text data. Relevant invalid text will not be deleted, it will still be retained, but it will not be used for labeling.

[0057] In addition, the text filtering rules will preset some rules to deal with some common invalid text data. For example: the whole sentence is "666", "23333", "good", "not bad", "general" and so on.

[0058] S02: Split the text into words and short sentences. According to the results screened out in step S01, the text is split into multiple words or short sentences according to grammatical rules. Multiple words and short sentences split from the same text will still be displayed together in the labeling stage, because there may be context dependencies between wor...

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Abstract

The invention belongs to the technical field of natural language processing, and discloses a text labeling method and system. According to the text labeling method and system of the invention, invalidtexts are filtered out through a custom rule; an effective text is split, specifically, the effective text is split into words and short sentences; corresponding attribute labels and sentiments are divided according to the split words and phrases; the attribute labels and the sentiments form an association relationship, so that effective data for supervised learning of a model can be generated. The text labeling system comprises a data filtering module, a labeling module, a data tracking statistics module, a data review module, a user configuration module and a self-starting model training module. The text labeling method and system provided by the invention can be suitable for various text labeling scenes, and provide a simpler, more convenient and more efficient labeling mode. With thetext labeling method and system of the invention adopted, a user operation process and an information filtering process are simplified; in a process from text input to generation model, assembly linework is formed, and overall working efficiency is improved.

Description

technical field [0001] The invention belongs to the technical field of natural language processing, and in particular relates to a text labeling method and system. Background technique [0002] At present, the closest existing technology: In recent years, driven by technologies and needs such as search, information extraction, and machine translation, natural language processing technology has rapidly developed into an independent discipline and has attracted much attention. However, it is still very difficult to interact with computers through natural language, not only to teach the computer how to recognize natural language, but also to correct the wrong recognition of the computer. How to make machines better understand natural language has always been a problem that experts and scholars are committed to solving. [0003] In layman's terms, when a computer understands natural language, it actually understands the meaning of the corpus. But there are many corpus, and cor...

Claims

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Application Information

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IPC IPC(8): G06F16/33G06F16/335G06F40/205G06F40/117
CPCG06F16/3344G06F16/335
Inventor 刘宝强肖云飞
Owner 深圳数阔信息技术有限公司