A Combinational Method to Determining Identical Entities from Heterogeneous Knowledge Graphs

With the increasing demand for intelligent services, knowledge graph technologies have attracted much attention. Various application-specific knowledge bases have been developed in industry and academia. In particular, open knowledge bases play an important role for constructing a new knowledge base...

Full description

Saved in:
Bibliographic Details
Published inJournal of information science theory and practice Vol. 6; no. 3; pp. 6 - 15
Main Author Kim, Haklae
Format Journal Article
LanguageEnglish
Published Daejeon Korea Institute of Science and Technology Information 01.09.2018
한국과학기술정보연구원
Subjects
Algorithms
entity consolidation
Expert systems
Feature extraction
knowledge creation
knowledge extraction
knowledge graph
knowledge interlinking
문헌정보학
Online AccessGet full text

Cover

More Information
Summary:With the increasing demand for intelligent services, knowledge graph technologies have attracted much attention. Various application-specific knowledge bases have been developed in industry and academia. In particular, open knowledge bases play an important role for constructing a new knowledge base by serving as a reference data source. However, identifying the same entities among heterogeneous knowledge sources is not trivial. This study focuses on extracting and determining exact and precise entities, which is essential for merging and fusing various knowledge sources. To achieve this, several algorithms for extracting the same entities are proposed and then their performance is evaluated using real-world knowledge sources.
Bibliography:https://www.koreascience.kr/article/JAKO201831960580568.pdf
ISSN:2287-9099
2287-4577
DOI:10.1633/JISTaP.2018.6.3.1