CoEPinKB: A Framework to Understand the Connectivity of Entity Pairs in Knowledge Bases

J. G. Jiménez, Luiz André Portes Paes Leme, M. Casanova
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引用次数: 3

Abstract

A knowledge base, expressed using the Resource Description Framework (RDF), can be viewed as a graph whose nodes represent entities and whose edges denote relationships. The entity relatedness problem refers to the problem of discovering and understanding how two entities are related, directly or indirectly, that is, how they are connected by paths in a knowledge base. Strategies designed to solve the entity relatedness problem typically adopt an entity similarity measure to reduce the path search space and a path ranking measure to order and filter the list of paths returned. This paper presents a framework, called CoEPinKB, that supports the empirical evaluation of such strategies. The proposed framework allows combining entity similarity and path ranking measures to generate different path search strategies. The main goals of this paper are to describe the framework and present a performance evaluation of nine different path search strategies.
CoEPinKB:一个理解知识库中实体对连通性的框架
使用资源描述框架(RDF)表示的知识库可以看作是一个图,其节点表示实体,其边表示关系。实体关联问题是指发现和理解两个实体是如何直接或间接关联的问题,即它们是如何通过知识库中的路径连接起来的问题。解决实体关联问题的策略通常采用实体相似度度量来减少路径搜索空间,采用路径排序度量来对返回的路径列表进行排序和过滤。本文提出了一个名为CoEPinKB的框架,该框架支持对此类策略进行实证评估。该框架允许结合实体相似度和路径排序度量来生成不同的路径搜索策略。本文的主要目标是描述该框架,并对九种不同的路径搜索策略进行性能评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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