汉语名词语义特征小型数据库构建与应用的初步研究

发布时间：2018-01-18 11:13

本文关键词：汉语名词语义特征小型数据库构建与应用的初步研究　出处：《南京医科大学》2015年硕士论文　论文类型：学位论文

【摘要】：目的:构建汉语名词语义特征模型,为临床言语治疗提供量化和可视化语义特征数据库。方法:以60个常见名词概念为刺激词,对健康受试者实施语义特征提名,采集各概念的语义特征条目,继而根据汉语语义特征分型方案对条目进行分类。最后以R软件实施分类数据可视化、聚类和统计检验。结果:1、根据语义特征进行的概念聚类与经验性分类结果基本一致,语义特征可以反映概念间语义关系。2、不同领域概念的语义认知处理具有类型偏向性,生物领域概念具有更多的感觉信息特征,而非生物领域概念则具有更多的功能用途特征。3、秩次居于首位的语义特征,在分类范畴型显著高。结论:根据汉语语义特征数据建立的模型可以有效反映概念语义结构,有助于根据量化指标提取语义训练素材。目的:分析认知功能障碍患者的语义特征分布特点,验证汉语语义特征分型方案的合理性。方法:以60个常见名词概念为刺激词,对失用症患者实施语义特征提名,采集各概念的语义特征条目,继而根据汉语语义特征分型方案对条目进行分类。最后以R软件实施分类数据可视化和统计检验。结果:在概念领域水平,两名患者表现出相似的模式,功能用途型特征的改善明显,在治疗后非生物领域概念的功能用途型特征显著高于预期。与正常受试者的语义分布模型比较发现,第二次测试时,两名患者在生物领域语义特征类型偏向性降低,而非生物领域的类型偏向性在增加。结论:汉语语义特征分型方案有助于评估患者的语义特征分布状态,提供康复治疗线索。
[Abstract]:Objective: to construct a semantic feature model of Chinese nouns to provide a quantitative and visual semantic feature database for clinical speech therapy. Methods: sixty common noun concepts were used as stimuli. The healthy subjects were nominated for semantic features, and the semantic feature items of each concept were collected. Then the items were classified according to the Chinese semantic feature classification scheme. Finally, the classification data visualization was implemented with R software. Clustering and statistical test. Result: 1, the concept clustering according to semantic features is basically consistent with empirical classification results, semantic features can reflect the semantic relationship between concepts. 2. Semantic cognitive processing of different domain concepts has type bias, biological domain concepts have more sensory information characteristics, and non-biological domain concepts have more functional use characteristics. Rank is the most important semantic feature, which is significantly higher in classification category. Conclusion: the model based on Chinese semantic feature data can effectively reflect the conceptual semantic structure. Objective: to analyze the distribution characteristics of semantic features in patients with cognitive dysfunction. Methods: 60 common noun concepts were used as stimulus words to nominate the semantic features of the patients with apraxia and to collect the semantic feature entries of each concept. Then the items are classified according to the Chinese semantic feature classification scheme. Finally, the classification data visualization and statistical test are implemented with R software. Results: at the conceptual level, the two patients showed similar patterns. The functional use-type features were significantly improved after treatment. Compared with the semantic distribution model of normal subjects, the functional use-type features of the non-biological domain concept were significantly higher than expected. Two patients in the biological domain semantic feature type bias decreased, while the non-biological domain type bias is increasing. Conclusion: Chinese semantic feature classification scheme is helpful to assess the semantic feature distribution of patients. Provide clues to rehabilitation treatment.
【学位授予单位】：南京医科大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：R49;TP311.13

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