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Journal Article
Graph-Based Knowledge Consolidation in Ontology Population
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- Authors
- Pum Mo RYU, Myung-Gil JANG, Hyun-Ki KIM, So-Young PARK
- Issue Date
- 2013-09
- Citation
- IEICE Transactions on Information and Systems, v.E96.D, no.9, pp.2139-2142
- ISSN
- 0916-8532
- Publisher
- 일본, 전자정보통신학회 (IEICE)
- Language
- English
- Type
- Journal Article
- Abstract
- We propose a novel method for knowledge consolidation based on a knowledge graph as a next step in relation extraction from text. The knowledge consolidation method consists of entity consolidation and relation consolidation. During the entity consolidation process, identical entities are found and merged using both name similarity and relation similarity measures. In the relation consolidation process, incorrect relations are removed using cardinality properties, temporal information and relation weight in given graph structure. In our experiment, we could generate compact and clean knowledge graphs where number of entities and relations are reduced by 6.1% and by 17.4% respectively with increasing relation accuracy from 77.0% to 85.5%. Copyright © 2013 The Institute of Electronics, Information and Communication Engineers.
- KSP Keywords
- Consolidation process, Graph-based, Information and communication, Knowledge Graph, Relation Extraction, graph structure, novel method, ontology population, similarity measure, temporal information