- Volume 12 Issue 1
DOI QR Code
Author Entity Identification using Representative Properties in Linked Data
대표 속성을 이용한 저자 개체 식별
- Received : 2011.12.13
- Accepted : 2011.12.29
- Published : 2012.01.28
In recent years, Linked Data that is published under an open license shows increased growth rate and comes into the spotlight due to its interoperability and openness especially in government of developed countries. However there are relatively few out-links compared with its entire number of links and most of links refer a few hub dataset. These occur because of absence of technology that identifies entities in Linked data. In this paper, we present an improved author entity resolution method that using representative properties. To solve problems of previous methods that utilizes relation with other entities(owl:sameAs, owl:differentFrom and so on) or depends on Curation, we design and evaluate an automated realtime resolution process based on multi-ontologies that respects entity's type and its logical characteristics so as to verify entities consistency. The evaluation of author entity resolution shows positive results (The average of K measuring result is 0.8533.) with 29 author information that has obtained confirmation.
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