Application of Kernels to Link Analysis: First Results
Application of Kernels to Link Analysis: First Results
复制标题
DOI：
--
复制
发表时间：
2004
期刊：
影响因子：
--
通讯作者：
Takahiko Ito;M. Shimbo;Taku Kudo;Yuji Matsumoto
中科院分区：
文献类型：
--
作者：
Takahiko Ito;M. Shimbo;Taku Kudo;Yuji Matsumoto
探讨了核方法在链接分析中的应用。我们认为，一个家庭的核心图提供了一个统一的角度对链接分析提出的三个措施：相关性，全球重要性和相对重要性。由内核提供的框架将相对重要性建立为相关性和全局重要性之间的中间体，其中相关性和重要性之间的偏差自然地由表征各个内核的参数控制。这些措施的属性进行了实验评估使用真实世界的网络书目引文。
The application of kernel methods to link analysis is explored. We argue that a family of kernels on graphs provides a unified perspective on the three measures proposed for link analysis: relatedness, global importance, and relative importance. The framework provided by the kernels establishes relative importance as an intermediate between relatedness and global importance, in which the bias between relatedness and importance is naturally controlled by a parameter characterizing individual kernels. An experimental evaluation of the property of these measures is carried out using a real-world network of bibliographic citations.