基于知识图谱的知识推理方法概述

Ignacio Villegas Vergara, Liza Chung Lee
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引用次数: 0

摘要

当今世界,互联网技术及其实施模式发展迅速,导致互联网数据规模呈指数级增长。这些数据蕴含着大量宝贵的知识。在特定的环境背景下,如何有效地组织和表达知识,并进行全面的计算和分析,已经引起了人们的极大关注和发展。在知识图谱研究领域,利用知识图谱进行知识推理已成为一个突出的重点领域。它在垂直搜索、智能应答和其他各种应用领域具有重要意义。本文将围绕推理的基本原理展开讨论。面向知识图谱的知识推理方法主要是通过利用已有知识推导新知识或检测错误知识。与传统的知识推理方法相比,知识图谱所采用的知识推理技术具有简洁、适应性强和灵活的知识表示方式等特点,因而具有更大的多样性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Schematic Review of Knowledge Reasoning Approaches Based on the Knowledge Graph
In the contemporary world, the Internet technology and its implementation mode are advancing at a swift pace, leading to an exponential growth in the scale of Internet data. This data contains a significant amount of valuable knowledge. The effective organization and articulation of knowledge, as well as the ability to conduct thorough calculations and analyses, have garnered significant attention and developments within a particular environmental context. The utilization of knowledge graphs for knowledge reasoning has emerged as a prominent area of focus within the realm of knowledge graph research. It holds substantial significance in the realm of vertical search, intelligent answering, and various other applications. This article will be centered on fundamental principles of reasoning. The approach of knowledge reasoning oriented towards knowledge graphs is focused on the derivation of novel knowledge or the detection of erroneous knowledge through the utilization of pre-existing knowledge. In contrast to conventional knowledge reasoning approaches, the knowledge reasoning technique employed in knowledge graphs is characterized by greater diversity, owing to the succinct, adaptable, and flexible representation of knowledge.
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