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Academic field data correlation prediction method based on deep learning and computer

A data correlation, deep learning technology, applied in the field of computer network data prediction, can solve the problems of low accuracy, not considering the impact of academic word vector prediction results, long prediction cycle, etc., to achieve the effect of fast and accurate prediction

Active Publication Date: 2019-09-06
GLOBAL TONE COMM TECH
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Problems solved by technology

Existing academic field correlation prediction methods have the problems of long period and low accuracy in realizing field-related prediction
[0005] To sum up, the problems existing in the existing technology are: the existing academic field correlation prediction methods have a long period of field-related prediction and low accuracy.
[0006] Difficulty in solving the above technical problems: Existing prediction methods are based on the similarity of nodes, topology, and network content information, etc., but these do not reflect the interconnection between scholars very well, and do not consider the relationship between word vectors in the academic field. Impact on Forecast Results

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  • Academic field data correlation prediction method based on deep learning and computer
  • Academic field data correlation prediction method based on deep learning and computer
  • Academic field data correlation prediction method based on deep learning and computer

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[0045] In order to make the object, technical solution and advantages of the present invention more clear, the present invention will be further described in detail below in conjunction with the examples. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0046] The invention can be used to solve applications such as automatic recommendation of scholars, papers, and patents in related fields in mining and analysis of scientific and technological information; first, collect data such as papers and patents in the academic field; then, use word vector technology of deep learning to train academic Field word vector; finally, for a given field, other semantically related fields can be predicted according to the word vector, so as to realize the prediction of related academic fields.

[0047] The technical solution of the present invention will be described in detail below in conj...

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Abstract

The invention belongs to the technical field of computer network data prediction, and discloses an academic field data correlation prediction method based on deep learning, and a computer. The methodcomprises steps of collecting public general data, and paper and patent data in the academic field; training an academic field word vector on the academic corpus by utilizing a word vector technologyof deep learning; for a given field, predicting other fields related to semantics according to the word vectors, and achieving prediction of related academic fields. The system comprises a data collection module used for collecting public data; the word vector training module is used for training academic field word vectors on the academic corpus by utilizing a word vector technology of deep learning; and the academic domain prediction module is used for predicting other semantically related domains according to the word vectors for a given domain to realize prediction of the related academicdomains. According to the method, the academic field word vector based on deep learning is constructed, and field-related rapid and accurate prediction is realized by means of the word vector.

Description

technical field [0001] The invention belongs to the technical field of computer network data prediction, and in particular relates to a deep learning-based data correlation prediction method in the academic field and a computer. Background technique [0002] Currently, the closest prior art: [0003] As scientific research is widely carried out in academia and industry, scholars have created a large number of scientific research results in a steady stream, so academic big data came into being. In academic big data, there are different academic subjects and various academic relationships formed between them, among which the cooperative relationship between scholars is the most common and important, especially in the research of interdisciplinary issues, between scholars from different fields The increasing cooperation among enterprises makes the research on the prediction of cooperative relationship more and more important. [0004] However, in the existing technologies, mo...

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Application Information

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IPC IPC(8): G06F16/35G06F17/27G06K9/62
CPCG06F16/35G06F40/289G06F18/214
Inventor 隗公程万洪波程国艮
Owner GLOBAL TONE COMM TECH
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