本文關(guān)鍵詞：漢語(yǔ)動(dòng)詞語(yǔ)義特征建模與分析　出處：《中國(guó)康復(fù)醫(yī)學(xué)雜志》2016年04期 　論文類(lèi)型：期刊論文

  更多相關(guān)文章： 動(dòng)詞概念 論元結(jié)構(gòu) 語(yǔ)義特征訓(xùn)練 言語(yǔ)語(yǔ)言治療 康復(fù)

【摘要】：目的:通過(guò)構(gòu)建漢語(yǔ)動(dòng)詞語(yǔ)義特征常模,為臨床言語(yǔ)治療提供量化和可視化的語(yǔ)義特征數(shù)據(jù)庫(kù)。方法:選擇30個(gè)日常生活常用動(dòng)詞作為刺激詞,采集健康人的語(yǔ)義特征,并進(jìn)行條目編碼,然后根據(jù)漢語(yǔ)語(yǔ)義特征分型方案對(duì)其進(jìn)行分類(lèi)。統(tǒng)計(jì)軟件采用R軟件進(jìn)行數(shù)據(jù)可視化和統(tǒng)計(jì)檢驗(yàn)。結(jié)果:(1)動(dòng)詞的語(yǔ)義特征以功能用途類(lèi)顯著。(2)動(dòng)詞首位秩次的語(yǔ)義特征以功能用途類(lèi)顯著。(3)一論元結(jié)構(gòu)動(dòng)詞以?xún)?nèi)省特征顯著。結(jié)論:根據(jù)漢語(yǔ)語(yǔ)義特征數(shù)據(jù)建立的模型可以有效反映概念語(yǔ)義結(jié)構(gòu),有助于根據(jù)量化指標(biāo)提取語(yǔ)義訓(xùn)練素材。
[Abstract]:Objective: to provide a quantitative and visual semantic feature database for clinical speech therapy by constructing the Chinese verb semantic feature norm. Methods: 30 verbs commonly used in daily life were selected as stimuli. The semantic features of healthy people were collected and the items were coded. Then it was classified according to the Chinese semantic feature classification scheme. The statistical software R was used to visualize and test the data. The results showed that the semantic feature of the verb was significant in the functional use category. The semantic features of the first rank of verbs are significant within the verb of functional use class. Conclusion: the model based on the semantic feature data of Chinese can effectively reflect the conceptual semantic structure. It is helpful to extract the semantic training material according to the quantization index.
【作者單位】： 南京醫(yī)科大學(xué)附屬第一醫(yī)院康復(fù)醫(yī)學(xué)科;
【基金】：江蘇省科技支撐計(jì)劃(BE2012675) 國(guó)家自然科學(xué)基金資助項(xiàng)目(81171854)
【分類(lèi)號(hào)】：R493
【正文快照】： 人類(lèi)通過(guò)不同的語(yǔ)句進(jìn)行信息傳遞及交流,而成。其中動(dòng)詞在句中的作用尤為關(guān)鍵,因其不僅攜語(yǔ)句是通過(guò)不同性質(zhì)的詞語(yǔ)(如名詞、動(dòng)詞、形容詞帶重要信息,而且在句子結(jié)構(gòu)形成中有重要作用[1]。等)在句中承擔(dān)不同的語(yǔ)法成分而合理的組合而也就是說(shuō),動(dòng)詞通常攜帶論元,不僅表現(xiàn)出語(yǔ)義，

本文編號(hào)：1408893