深度语义搜索的本体-图形机制

IF 0.5 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS

AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS Pub Date : 2022-10-04 DOI:10.3103/S0005105522040057

A. A. Lebedev, A. S. Gavrilkina, N. V. Maksimov, O. L. Golitsina, K. V. Monankov

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引用次数: 1

摘要

在专注于主要活动认知过程的信息支持的人机文档检索框架中，讨论了基于图的深度语义搜索机制。在由全文构建的图上，给出了与用户认知状态相对应的例子的应用机制。本文将图搜索机制应用于文本阅读过程，对其在检索任务中的有效性进行了比较评价。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Onto-Graphic Mechanisms for Deep Semantic Search

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Onto-Graphic Mechanisms for Deep Semantic Search

In human-machine document retrieval frameworks focused on information support for main activity cognitive processes, onto-graph-based mechanisms for deep semantic search are discussed. The mechanisms of the application of examples corresponding to users’ cognitive states are given on graphs constructed from full texts. The paper gives a comparative evaluation of graph search mechanisms effectiveness in retrieval tasks, as applied to text reading processes.

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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.