The Enslaved Dataset: A Real-world Complex Ontology Alignment Benchmark using Wikibase
The Enslaved Dataset: A Real-world Complex Ontology Alignment Benchmark using Wikibase
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Enslaved 数据集:使用 Wikibase 的现实世界复杂本体对齐基准
DOI:
10.1145/3340531.3412768
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发表时间:
2020
期刊:
影响因子:
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通讯作者:
Dean Rehberger
中科院分区:
文献类型:
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作者:
Lu Zhou;C. Shimizu;P. Hitzler;Alicia M. Sheill;Seila Gonzalez Estrecha;Catherine Foley;D. Tarr;Dean Rehberger
Ontology alignment has taken a critical place for helping heterogeneous resources to interoperate. It has been studied for over a decade, and over that time many alignment systems and methods have been developed by researchers to find simple 1:1 equivalence matches between two ontologies. However, very few alignment systems focus on finding complex correspondences. Even if the complex alignment systems are developed, the performance of finding complex relations still has a lot of room for improvement. One reason for this limitation may be that there are still few applicable alignment benchmarks that contain such complex relationships that can raise researchers' interests. In this paper, we propose a real-world dataset from the Enslaved project as a potential complex alignment benchmark. The benchmark consists of two resources, the Enslaved Ontology along with a Wikibase repository holding a large number of instance data from the Enslaved project, as well as a manually created reference alignment between them. The alignment was developed in consultation with domain experts in the digital humanities. The alignment not only includes simple 1:1 equivalence correspondences, but also more complex m:n equivalence and subsumption correspondences and are provided in both Expressive and Declarative Ontology Alignment Language (EDOAL) format and rule syntax. The Enslaved benchmark has been incorporated into the Ontology Alignment Evaluation Initiative (OAEI) 2020 and is completely free for public use to assist the researchers in developing and evaluating their complex alignment algorithms.
DOI:
10.1007/s10817-014-9305-1
发表时间:
2014-10-01
期刊:
JOURNAL OF AUTOMATED REASONING
影响因子:
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作者:
Glimm, Birte;Horrocks, Ian;Wang, Zhe
通讯作者:
Wang, Zhe