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Unstructured data decision method and apparatus based on deep learning

An unstructured data and deep learning technology, applied in the field of unstructured data judgment methods and devices, can solve the problems of rapid changes in unstructured data, low analysis and decision-making efficiency, and long analysis time, so as to achieve timely data analysis and judgment, Fast change, the effect of realizing the amount of data

Active Publication Date: 2018-05-04
PEKING UNIV SHENZHEN GRADUATE SCHOOL
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AI Technical Summary

Problems solved by technology

[0003] In traditional technology, due to the characteristics of unstructured data such as rapid change and inconsistent structure, it takes a long time to analyze unstructured data. Generally, offline analysis of historical data is performed, and the efficiency of analysis and decision-making is low.

Method used

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  • Unstructured data decision method and apparatus based on deep learning
  • Unstructured data decision method and apparatus based on deep learning
  • Unstructured data decision method and apparatus based on deep learning

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Embodiment Construction

[0041] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0042] Such as figure 1 As shown, in one embodiment, an application environment diagram of an unstructured data decision method and device based on deep learning is provided, the application environment includes a data collection device 110 and a server 120, wherein the data collection terminal 110 can pass The network communicates with the server 120 . Data acquisition equipment may include camera terminals, network terminals, data storage media, etc., wherein camera terminals may capture unstructured data such as video data, image data, and audio data; network terminals may acquire network data,...

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Abstract

The present invention relates to an unstructured data decision method based on deep learning. The method specifically comprises: obtaining a trained deep learning neural network model, wherein the trained deep learning neural network model is a multi-factor joint decision neural network model trained by multi-factor training sample data; receiving online real-time collected clue data, wherein theclue data comprises a plurality of data types of unstructured data; carrying out conjoint analysis on the obtained clue data through a trained deep learning neural network model, and extracting feature clue information that is favorable to the decision; deciding the clue data according to the feature clue information, and generating a decision result; and feeding back the decision result. The method disclosed by the present invention can carry out more efficient and timely decision analysis on the unstructured data and implement online real-time analysis.

Description

technical field [0001] The present invention relates to the technical field of artificial intelligence, in particular to a deep learning-based unstructured data judgment method and device. Background technique [0002] Compared with structured data (that is, row data, which is stored in the database and can be logically expressed by a two-dimensional table structure), the data that is not convenient to be represented by a two-dimensional logical table of the database is called unstructured data. Including all formats of office documents, texts, pictures, subsets of standard common markup language XML, HTML, various reports, images and audio / video information, etc. Unstructured data has the characteristics of large data volume, rapid change, variety, rich and complex content, and inconsistent structure. [0003] In traditional technology, due to the characteristics of unstructured data such as rapid change and inconsistent structure, it takes a long time to analyze unstructu...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/04G06F17/30
CPCG06F16/35G06N3/044
Inventor 朱跃生罗桂波
Owner PEKING UNIV SHENZHEN GRADUATE SCHOOL
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