一种无先验知识的知识图探索方法

Ariani Indrawati, Zaenal Akbar, D. Rini, Aris Yaman, Y. Kartika, D. R. Saleh
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引用次数: 1

摘要

各个部门现在广泛采用知识图来描述和共享其组织知识库。不幸的是,大多数知识共享系统都是为领域专家设计的。让非专业人士很难理解内容和探索图表。解决这个问题的方法是使用机器辅助知识图探索方法。本文介绍了一种知识探索方法,用于系统、高效地导航知识图谱。首先,我们基于现有的通用模式对知识图进行建模。其次,我们创建了一种搜索树技术来有效地导航知识图谱。该算法通过确定知识图探索路径来解决这一问题。我们利用辣椒的形态特征知识库来评估这种方法。图探索的目标是正确识别辣椒品种。因此,即使在搜索的起始点事先未知的情况下,所提出的机制也能达到较高的精度。
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A Knowledge Graph Exploration Method with No Prior Knowledge
Various sectors now widely adopt knowledge graphs to describe and share their organizational knowledge bases. Unfortunately, the majority of knowledge-sharing systems are designed for domain experts. Making it extremely difficult for a non-expert to understand the content and explore the graph. A solution to this issue is using a machine-assisted knowledge graph exploration approach. This research introduces a knowledge exploration method to systematically and efficiently navigate a knowledge graph. First, we modeled the knowledge graphs based on the existing common schema. Second, we created a search tree technique to navigate the knowledge graph efficiently. The algorithm solves the problem by determining the path of knowledge graph exploration. We evaluated the method using a knowledge base of morphological characteristics of Capsicum. The goal of graph exploration was to identify a Capsicum species correctly. As a result, the proposed mechanism can achieve high precision, even when the search’s starting point is unknown beforehand.
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