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面向文本的本体学习方法

, PP. 236-244

Keywords: 人工智能,本体学习,主动学习,模式匹配,频繁项挖掘,启发式学习

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Abstract:

借助文本预处理工具Gate和通用本体WordNet,采用统计、频繁项挖掘、模式匹配、启发式学习和主动学习等技术,学习本体基元——概念(含实例)、概念间的分类关系、概念间的语义关系和概念属性,其中概念属性学习为本文首次提出。实验结果表明,本文方法改善了概念语义排歧效果,丰富了短语概念学习与语义关系学习,提高了本体自动构建的准确度,降低了本体学习的代价。

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