利用人工智能方法自动搜索大学员工的科学论文

Nadezhda I. Gallini, P. Chetyrbok, D. T. Kamornitskiy, Nikolaj S. Motuz
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引用次数: 0

摘要

本文提出了一个集成的大学研究活动智能系统模型(IIS of URAs),它提供了科学论文的搜索和员工排名。所设计的神经网络通过Scikit-Learn包工作,并用于智能系统模型的实现。这个包允许智能系统搜索作者科学论文正确和快速。该系统使用基于Keras包的神经网络进行训练。本文的作者对员工排名的进一步数据预测和外推进行了研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automation of Search for University Employees Scientific Papers Using Artificial Intelligence Methods
The paper substantiates a model of an integrated intelligent system of university research activities (IIS of URAs), which provides for a search for scientific papers and ranks employees. Designed neural network works via the Scikit-Learn package and is used in the implementation of the intelligent system model. This package allows the intelligent system to search for authors scientific papers correctly and quickly. The system is trained using a neural network based on the Keras package. The authors of the article conducted research on further data forecasting and extrapolation for ranking employees.
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