排序方式： 共有5条查询结果，搜索用时 15 毫秒
1
1.
2.
3.
《Journal of Informetrics》2020,14(2):101013
A citation is a well-established mechanism for connecting scientific artifacts. Citation networks are used by citation analysis for a variety of reasons, prominently to give credit to scientists’ work. However, because of current citation practices, scientists tend to cite only publications, leaving out other types of artifacts such as datasets. Datasets then do not get appropriate credit even though they are increasingly reused and experimented with. We develop a network flow measure, called DataRank, aimed at solving this gap. DataRank assigns a relative value to each node in the network based on how citations flow through the graph, differentiating publication and dataset flow rates. We evaluate the quality of DataRank by estimating its accuracy at predicting the usage of real datasets: web visits to GenBank and downloads of Figshare datasets. We show that DataRank is better at predicting this usage compared to alternatives while offering additional interpretable outcomes. We discuss improvements to citation behavior and algorithms to properly track and assign credit to datasets. 相似文献
4.
分析数据集合访问的过程,针对.NET架构的实际应用,根据.NET架构提供的类和对象,提出数据访问中间件的结构。并使用外观模式、工厂模式、单件模式实现此中间件。 相似文献
5.
基于主题地图的异构知识集成* 总被引：2，自引：1，他引：2
大型企业和科研机构所处理的信息通常是分布式的，这些信息除了分散在不同的数据库中之外，还以类型各异的文档形式独立存在。为了抽取信息资源中隐含的知识，需要探索数据库及存档文件，把其中有用的知识单元一一挑选出来。为了从整体上对抽取的知识加以把握，还需要把这些知识片段有机地整合起来。本文提出基于主题地图的知识集成系统TMKIS，将信息资源的本体表示规范、存储方式、自动抽取方式、合法性验证以及浏览方式有机地结合起来，利用主题地图技术，处理异构的信息资源，实现异构知识集成的目标。 相似文献
1