IEICE Transactions on Information and Systems
Online ISSN : 1745-1361
Print ISSN : 0916-8532
Regular Section
Graph-Based Knowledge Consolidation in Ontology Population
Pum Mo RYUMyung-Gil JANGHyun-Ki KIMSo-Young PARK
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2013 Volume E96.D Issue 9 Pages 2139-2142


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%.

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© 2013 The Institute of Electronics, Information and Communication Engineers
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