Difference between revisions of "Zhishi.links Results for OAEI 2011"
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|Subject=Ontology Alignment | |Subject=Ontology Alignment | ||
|Authors=Xing Niu, Shu Rong, Yunlong Zhang, Haofen Wang, | |Authors=Xing Niu, Shu Rong, Yunlong Zhang, Haofen Wang, | ||
| − | |Series=Ontology Matching | + | |Series=Journal of Ontology Matching |
|Year=2011 | |Year=2011 | ||
|Abstract=This report presents the results of Zhishi.links, a distributed instance matching system, for this year’s Ontology Alignment Evaluation Initiative (OAEI) campaign. We participate in Data Interlinking track (DI) of IM@OAEI2011. In this report, we briefly describe the architecture and matching strategies of Zhishi.links, followed by an analysis of the results. | |Abstract=This report presents the results of Zhishi.links, a distributed instance matching system, for this year’s Ontology Alignment Evaluation Initiative (OAEI) campaign. We participate in Data Interlinking track (DI) of IM@OAEI2011. In this report, we briefly describe the architecture and matching strategies of Zhishi.links, followed by an analysis of the results. | ||
Revision as of 14:52, 28 June 2018
| Zhishi.links Results for OAEI 2011 | |
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Zhishi.links Results for OAEI 2011
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| Bibliographical Metadata | |
| Subject: | Ontology Alignment |
| Year: | 2011 |
| Authors: | Xing Niu, Shu Rong, Yunlong Zhang, Haofen Wang |
| Venue | Journal of Ontology Matching |
| Content Metadata | |
| Problem: | No data available now. |
| Approach: | No data available now. |
| Implementation: | No data available now. |
| Evaluation: | No data available now. |
Abstract
This report presents the results of Zhishi.links, a distributed instance matching system, for this year’s Ontology Alignment Evaluation Initiative (OAEI) campaign. We participate in Data Interlinking track (DI) of IM@OAEI2011. In this report, we briefly describe the architecture and matching strategies of Zhishi.links, followed by an analysis of the results.
Conclusion
In this report, we have presented a brief description of Zhishi.links, an instance matching system. We have introduced the architecture of our system and specific techniques we used. Also, the results have been analyzed in detail and several guides for improvements have been proposed.
Future work
We look forwards to build an instance matching system with better performance and higher stability in the future.
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