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OWL本体归纳查询应答的统计学习

Statistical Learning for Inductive Query Answering on OWL Ontologies
课程网址: http://videolectures.net/iswc08_damato_stiqa/  
主讲教师: Claudia d'Amato
开课单位: 巴里大学
开课时间: 2008-11-24
课程语种: 英语
中文简介:
提出了为本体内的个体定义的一组新的参数化语言独立核函数。它们很容易与有效的统计学习方法相结合,用于诱导线性分类器,提供另一种执行分类的方法w.r.t.演绎推理。还提出了一种通过随机优化使内核参数适应知识库的方法。这使得能够在各种任务中利用统计学习,其中由于知识库的固有不完整性,归纳方法可以弥合标准方法的差距。在这项工作中,集成内核的系统已经在使用从标准存储库收集的真实本体进行近似查询回答的实验中进行了测试。
课程简介: A novel family of parametric language-independent kernel functions defined for individuals within ontologies is presented. They are easily integrated with efficient statistical learning methods for inducing linear classifiers that offer an alternative way to perform classification w.r.t. deductive reasoning. A method for adapting the parameters of the kernel to the knowledge base through stochastic optimization is also proposed. This enables the exploitation of statistical learning in a variety of tasks where an inductive approach may bridge the gaps of the standard methods due the inherent incompleteness of the knowledge bases. In this work, a system integrating the kernels has been tested in experiments on approximate query answering with real ontologies collected from standard repositories.
关 键 词: 参数化语言; 独立核函数; 统计学习
课程来源: 视频讲座网
最后编审: 2019-04-27:cwx
阅读次数: 54