为了提高文本挖掘的深度和精度,研究并提出了一种基于领域本体的语义文本挖掘模型.该模型利用语义角色标注进行语义分析,获取概念和概念间的语义关系,提高文本表示的准确度;针对传统的知识挖掘算法不能有效挖掘语义元数据库,设计了一种基于语义的模式挖掘算法挖掘文本深层的语义模式.实验结果表明,该模型能够挖掘文本数据库中的深层语义知识,获取的模式具有很强的潜在应用价值,设计的算法具有很强的适应性和可扩展性.%In order to improve the depth and accuracy of text mining, a semantic text mining model based on domain ontology is proposed. In this model, semantic role labeling is applied to semantic analysis so that the semantic relations can be extracted accurately. For the defect of traditional knowledge mining algorithms that can not effectively mine semantic meta database, an association patterns mining algorithm hased on semantic is designed and used to acquire the deep semantic association patterns from semantic meta database. Experimental results show that the model can mine deep semantic knowledge from text database. The pattern got has great potential applications, and the algorithm designed has strong adaptability and scalability.
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