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首页> 外文会议>Evolving and Adaptive Intelligent Systems (EAIS), 2012 IEEE Conference on >Elastic adaptive ontology matching on evolving folksonomy driven environment
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Elastic adaptive ontology matching on evolving folksonomy driven environment

机译：进化的民俗疗法驱动环境下的弹性自适应本体匹配

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摘要

Semantic networks can simulate the human complex frames in reasoning process providing efficient association and inference mechanisms. Ontology can be used to fill the gap between human and computational intelligence for a task domain. For an evolving environment it is important to understand what knowledge is required for a task domain with an adaptive ontology matching. To reflect the evolving knowledge this paper considers ontologies based on folksonomies according to a new concept structure called “Folksodriven” to represent folksonomies. Folksonomies are a set of terms that a group of users tagged content without a controlled vocabulary. A Folksodriven Structure Network (FSN), built from the relations among the Folksodriven tags, is presented as a folksonomy tags suggestions for the user to solve the problems inherent in an uncontrolled vocabulary of the folksonomy. It was observed that the properties of the FSN depend mainly on the nature, distribution, size and the quality of the reinforcing Folksodriven tags (FD tags). So, the studies on the transformational regulation of the FD tags are regarded to be important for an adaptive folksonomies classifications in an evolving environment used by Intelligent Systems. This paper discuss the deformation exhibiting linear behavior on FSN based on folksonomy tags chosen by different user on web site resources, this is a topic which has not been well studied so far. The discussion shows that the linear elastic constitutive equation possesses some leaning for the investigation. A constitutive law on FSN is investigated towards a systematic mathematical analysis on stress analysis and equations of motion for an evolving ontology matching on an environment defined by the users'' folksonomy choice. The adaptive ontology matching and the elastodynamics are merged to obtain what we can call the elasto-adaptative-dynamics methodology of the FSN.
机译：语义网络可以在推理过程中模拟人类复杂的框架，从而提供有效的关联和推理机制。本体可用于填补任务领域的人员和计算智能之间的空白。对于不断发展的环境，重要的是要了解具有自适应本体匹配的任务域需要哪些知识。为了反映不断发展的知识，本文根据称为“民俗驱动”的新概念结构（代表民俗分类法）考虑了基于民俗分类法的本体。 Folksonomies是一组术语，一组用户标记了内容而没有受控的词汇。从民俗驱动标签之间的关系构建的民俗驱动结构网络（FSN）作为民俗分类标签建议被提出，供用户解决民俗分类不受控制的词汇中固有的问题。观察到，FSN的特性主要取决于增强的民俗驱动标签（FD标签）的性质，分布，大小和质量。因此，在智能系统使用的不断发展的环境中，对FD标签的转换调控的研究被认为对于自适应民俗分类具有重要意义。本文基于不同用户在网站资源上选择的民俗分类标签，讨论了在FSN上表现出线性行为的变形，这是一个至今尚未很好研究的课题。讨论表明，线性弹性本构方程具有一定的研究意义。对FSN的本构定律进行了研究，以针对应力分析和运动方程进行系统的数学分析，以针对由用户的民俗疗法选择所定义的环境中不断发展的本体匹配。自适应本体匹配和弹性动力学被合并以获得我们可以称之为FSN的弹性自适应动力学方法。

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