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Confidence Value based Large Scale OWL Horst Ontology Reasoning
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신뢰 값 기반의 대용량 OWL Horst 온톨로지 추론

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Type
Academic journal
Author
Wan-Gon Lee (숭실대학교) Hyun-Kyu Park (숭실대학교) Batselem Jagvaral (숭실대학교) Young-Tack Park (숭실대학교)
Journal
Korean Institute of Information Scientists and Engineers Journal of KIISE Vol.43 No.5 KCI Excellent Accredited Journal
Published
2016.5
Pages
553 - 561 (9page)

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Confidence Value based Large Scale OWL Horst Ontology Reasoning
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Several machine learning techniques are able to automatically populate ontology data from web sources. Also the interest for large scale ontology reasoning is increasing. However, there is a problem leading to the speculative result to imply uncertainties. Hence, there is a need to consider the reliability problems of various data obtained from the web. Currently, large scale ontology reasoning methods based on the trust value is required because the inference-based reliability of quantitative ontology is insufficient. In this study, we proposed a large scale OWL Horst reasoning method based on a confidence value using spark, a distributed in-memory framework. It describes a method for integrating the confidence value of duplicated data. In addition, it explains a distributed parallel heuristic algorithm to solve the problem of degrading the performance of the inference. In order to evaluate the performance of reasoning methods based on the confidence value, the experiment was conducted using LUBM3000. The experiment results showed that our approach could perform reasoning twice faster than existing reasoning systems like WebPIE.
#빅데이터 #온톨로지 #추론 #스파크 #신뢰값 #OWL Horst #Big Data #Ontology #Reasoning #Spark #Confidence Value

Contents

요약
Abstract
1. 서론
2. 관련 연구
3. 신뢰값 기반 OWL Horst 추론
4. 실험
5. 결론
References

References (18)

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Auer, Sören, et al., "Dbpedia: A nucleus for a web of open data," Springer Berlin Heidelberg, 2007. google schola Etzioni, Oren, et al., "Unsupervised named-entity extraction from the web: An experimental study," Artificial intelligence 165.1, pp. 91-134, 2005. google schola Carlson, Andrew, et al., "Toward an Architecture for Never-Ending Language Learning," AAAI, Vol. 5, 2010. google schola Suchanek, Fabian M., Gjergji Kasneci, and Gerhard Weikum. "Yago: a core of semantic knowledge," Proc. of the 16th international conference on World Wide Web. ACM, 2007. google schola Ahmad, Khurshid, and Lee Gillam, "Automatic ontology extraction from unstructured texts," On the Move to Meaningful Internet Systems 2005: CoopIS, DOA, and ODBASE. Springer Berlin Heidelberg, pp. 1330-1346, 2005. google schola

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UCI(KEPA) : I410-ECN-0101-2016-569-002845457