期刊文献+

意欲形容词的语义特征分析 被引量:1

Semantic Analysis of the Conation Features of Adjectives in Chinese
下载PDF
导出
摘要 意欲性是个动态的概念,它要求有生命的施事主体对形容词所表达的性质、状态或程度不仅能够且必须在意志行为或动作行为的控制下向意欲主体所希望的方向发生改变。通过分析形容词入句后的语义指向,提取出几个基本语义特征:[生命度]、[可变度](包括自主和可控)、[自变/使成]、[本原]和[感情度]。意欲性包含三层含义:(1)形容词所表达的性状能够受意志行为或动作行为控制。(2)意欲主体所希望的方向。(3)性质或状态发生改变。 Conation is a dynamic concept.In specific contexts,it expresses the wish or desire that cognitive-subject wants to have,adjust or avoid the traits that the adjectives express.Conative-adjectives result from contexts,so the features could only be observed in the relationship between the structures of the sentences.Through analysis,four semantic features are concluded:[animacy],[controllable](in broad sense): including [volitional] and [controllable](in narrow sense),[self-varying/causative],[co-origin] and [affective].
作者 陈珺
出处 《华南农业大学学报(社会科学版)》 CSSCI 2011年第4期150-154,共5页 Journal of South China Agricultural University(Social Science Edition)
基金 国家社会科学规划基金一般项目(95BYY004)
关键词 意欲形容词 语义指向 语义特征 Conative-adjectives Semantic direction Semantic features
  • 相关文献

参考文献7

二级参考文献40

共引文献480

同被引文献32

  • 1邵敬敏,周芍.语义特征的界定与提取方法[J].外语教学与研究,2005,37(1):21-28. 被引量:53
  • 2吴力群.知识基因、知识进化与知识服务[J].现代情报,2005,25(6):177-179. 被引量:9
  • 3尚文倩,黄厚宽,刘玉玲,林永民,瞿有利,董红斌.文本分类中基于基尼指数的特征选择算法研究[J].计算机研究与发展,2006,43(10):1688-1694. 被引量:38
  • 4Weal, Mark J., Michaelides, Danius T., Page, Kevin R., De Roure,David C., Monger, Eloise and Gobbi, Mary. Semantic annotation ofubiquitous learning environments[J]. IEEE Transactions on LearningTechnologies, 2012,5 (2): 143-156.
  • 5Ting-Peng Liang, Yung-Fang Yang, Deng-Neng Chen, & Yi-ChengKu. A semantic-expansion approach to personalized knowledgerenommendation Original Research Article[J]. Decision SupportSystems, 2008, (3): 401-412.
  • 6Maged N. Kamel Boulos. Semantic Wikis: A ComprehensibleIntroduction with Examples from the Health SciencesfJ]. Journal ofEmerging Technologies in Web Intelligence,2009, (1): 94-96.
  • 7Jesus Soto Carrion, Elisa Garcia Gordo, & Salvador Sanchez-Alonso.Semantic learning object repositories[J]. International Journal ofContinuing Engineering Education and Life Long Learning, 2007, (17):432-446.
  • 8Hyun-seok Minjae Young Choi,Wesley De Neve, &Yong Man Ro.Bimodal fusion of low-level visual features and high-level semanticfeatures for near-duplicate video clip dfttection[J]. Signal Processing:Image Communication, 2011, 26(10): 612 - 627.
  • 9Yin-Hsi Kuo, Wen-Huang Cheng, Member, IEEE, Hsuan-Tien Lin,Memi.er, IEEE, and Winston H. Hsu. Unsupervised Semantic FeatureDiscovery for Image Object Retrieval and Tag Refinement[J]. IEEETransactions on Multimedia, 2012, 14⑷:1079-1090.
  • 10Khan, A., Baharudin, B., & Khan, K. Semantic Based FeaturesSelection and Weighting Method for Text Classification[DB/OL].http://www.utp.edu.my/estcon2010/images/docs/itsim-final-approved.pdf,2013-09-09.

引证文献1

二级引证文献9

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部