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Trend Ontology for Knowledge-based Trend Mining in textual Information

机译:基于知识的趋势挖掘在文本信息中的趋势本体论

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Providing ontologies for the automatic trend detection enhance the quality of trend predictions. However, in the case of dynamic and fuzzy expert knowledge like the knowledge used in trend detection, it is difficult to formalize knowledge unambiguously and in a static way. In this paper we report on our experiences in modeling and formalizing trend ontology for automatic knowledge-based trend detection by the example of market research, i.e. we describe the knowledge-based trend mining approach and requirements for trend ontology, discuss obstacles in modeling trend knowledge and outline three lightweight trend ontologies modeled.
机译:为自动趋势检测提供本体提高趋势预测的质量。然而,在动态和模糊专家知识的情况下,像潮流检测中使用的知识一样,难以明确地形式化知识并以静态的方式形式化。在本文中,我们通过市场研究的示例,向自动知识的趋势检测进行自动知识的趋势检测的建模和正式趋势本体的经验,即我们描述了基于知识的趋势挖掘方法和对趋势本体的要求,讨论了建模趋势知识的障碍并概述三个轻量级趋势本体建模。

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