科技信息语义处理的神经网络算法概念模型

IF 0.5 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS

AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS Pub Date : 2025-06-16 DOI:10.3103/S0005105525700529

S. M. Pistsov, V. A. Trusov

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引用次数: 0

摘要

从认知信息检索的角度考虑利用神经网络语言模型来提高互联网科技信息处理的效率。在现有科技创新分类系统的基础上，提出了一个概念模型来识别与信息需求对象相对应的主题领域。该模型基于坐标标引的原则，结合主题检测和跟踪方法，利用大型语言模型分析用户信息需求的信息空间，对互联网资源进行元搜索，对相关文档进行自动文摘和排序。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Conceptual Model of Neural Network Algorithmization of Semantic Processing of Scientific and Technical Information

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Conceptual Model of Neural Network Algorithmization of Semantic Processing of Scientific and Technical Information

The use of neural network language models to increase the efficiency of processing scientific and technical information (STI) on the Internet from the point of view of cognitive information retrieval is considered. A conceptual model is proposed to identify subject areas that corresponding to the object of information need based on existing STI classification systems. The model is based on the principles of coordinate indexing incorporating methods of detecting and tracking topics and the use of large language models to analyze the information space of the user’s information needs, metasearch of Internet resources, automatic abstracting and ranking of relevant documents.

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来源期刊

AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS COMPUTER SCIENCE, INFORMATION SYSTEMS-

自引率

40.00%

发文量

期刊介绍： Automatic Documentation and Mathematical Linguistics is an international peer reviewed journal that covers all aspects of automation of information processes and systems, as well as algorithms and methods for automatic language analysis. Emphasis is on the practical applications of new technologies and techniques for information analysis and processing.