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

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...

AI Technical Summary

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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