DEBUT 发表于 2025-3-21 19:15:50
书目名称Linked Data and Knowledge Graph影响因子(影响力)<br> http://impactfactor.cn/if/?ISSN=BK0586754<br><br> <br><br>书目名称Linked Data and Knowledge Graph影响因子(影响力)学科排名<br> http://impactfactor.cn/ifr/?ISSN=BK0586754<br><br> <br><br>书目名称Linked Data and Knowledge Graph网络公开度<br> http://impactfactor.cn/at/?ISSN=BK0586754<br><br> <br><br>书目名称Linked Data and Knowledge Graph网络公开度学科排名<br> http://impactfactor.cn/atr/?ISSN=BK0586754<br><br> <br><br>书目名称Linked Data and Knowledge Graph被引频次<br> http://impactfactor.cn/tc/?ISSN=BK0586754<br><br> <br><br>书目名称Linked Data and Knowledge Graph被引频次学科排名<br> http://impactfactor.cn/tcr/?ISSN=BK0586754<br><br> <br><br>书目名称Linked Data and Knowledge Graph年度引用<br> http://impactfactor.cn/ii/?ISSN=BK0586754<br><br> <br><br>书目名称Linked Data and Knowledge Graph年度引用学科排名<br> http://impactfactor.cn/iir/?ISSN=BK0586754<br><br> <br><br>书目名称Linked Data and Knowledge Graph读者反馈<br> http://impactfactor.cn/5y/?ISSN=BK0586754<br><br> <br><br>书目名称Linked Data and Knowledge Graph读者反馈学科排名<br> http://impactfactor.cn/5yr/?ISSN=BK0586754<br><br> <br><br>bioavailability 发表于 2025-3-22 00:10:27
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1865-0929 CSWS 2013, held in Shanghai, China in August 2013. The 14 revised full papers presented together with 6 short papers and 3 poster papers were carefully reviewed and selected from 48 submissions. The papers cover a wide range of topics, including semantic search, ontology reasoning, social semantic W无政府主义者 发表于 2025-3-22 12:18:57
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Searching Semantic Associations Based on Virtual Document,idea. To characterize the semantics of each association, a virtual document of each association is built with the help of a neighboring operation. A searching model of virtual documents of associations and a ranking schema are also discussed in this paper. Experiments show that our approach is feasible and efficient.anatomical 发表于 2025-3-22 17:22:19
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http://reply.papertrans.cn/59/5868/586754/586754_9.pngcondescend 发表于 2025-3-23 08:39:25
Evaluating Article Quality and Editor Reputation in Wikipedia, an efficient algorithm. We conduct experiments to validate the effectiveness of the proposed model. By leveraging the belief propagation between articles and editors, our approach obtains significant improvement over several alternative methods(SVM, LR, PR, CRF).