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焦点敏感算子“只”的量级用法和非量级用法 被引量:28
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作者 殷何辉 《语言教学与研究》 CSSCI 北大核心 2009年第1期49-56,共8页
本文从"只"的焦点敏感特性出发考察"只"在句子中的语义作用。以焦点敏感算子与焦点相互作用能否使焦点激发的选项构成量级序列为依据,区分了焦点敏感算子的量级用法和非量级用法,在此基础上说明算子"只"... 本文从"只"的焦点敏感特性出发考察"只"在句子中的语义作用。以焦点敏感算子与焦点相互作用能否使焦点激发的选项构成量级序列为依据,区分了焦点敏感算子的量级用法和非量级用法,在此基础上说明算子"只"有量级用法和非量级用法,并据此解释了与"只"相关的一些语言现象。 展开更多
关键词 焦点敏感算子 量级用法 量级用法
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徽州方言“物/物事”的量级用法 被引量:6
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作者 赵日新 《中国语文》 CSSCI 北大核心 2009年第3期248-254,共7页
本文描写徽州方言"物/物事"的量级用法,对"物/物事"由名词虚化为焦点敏感算子的动因、过程进行简要分析。"物/物事"语义关联的对象大多是数量词、时间词、时间名词或"子集名词",其作用是表示... 本文描写徽州方言"物/物事"的量级用法,对"物/物事"由名词虚化为焦点敏感算子的动因、过程进行简要分析。"物/物事"语义关联的对象大多是数量词、时间词、时间名词或"子集名词",其作用是表示主观小量、评述时间或范围、强调说话人对所陈述的事态在数量和范围等方面的主观评价。 展开更多
关键词 徽州方言 物/物事 量级用法 主观化
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Automatically Mining Application Signatures for Lightweight Deep Packet Inspection
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作者 鲁刚 张宏莉 +3 位作者 张宇 Mahmoud T. Qassrawi 余翔湛 彭立志 《China Communications》 SCIE CSCD 2013年第6期86-99,共14页
Automatic signature generation approaches have been widely applied in recent traffic classification.However,they are not suitable for LightWeight Deep Packet Inspection(LW_DPI) since their generated signatures are mat... Automatic signature generation approaches have been widely applied in recent traffic classification.However,they are not suitable for LightWeight Deep Packet Inspection(LW_DPI) since their generated signatures are matched through a search of the entire application data.On the basis of LW_DPI schemes,we present two Hierarchical Clustering(HC) algorithms:HC_TCP and HC_UDP,which can generate byte signatures from TCP and UDP packet payloads respectively.In particular,HC_TCP and HC_ UDP can extract the positions of byte signatures in packet payloads.Further,in order to deal with the case in which byte signatures cannot be derived,we develop an algorithm for generating bit signatures.Compared with the LASER algorithm and Suffix Tree(ST)-based algorithm,the proposed algorithms are better in terms of both classification accuracy and speed.Moreover,the experimental results indicate that,as long as the application-protocol header exists,it is possible to automatically derive reliable and accurate signatures combined with their positions in packet payloads. 展开更多
关键词 traffic classification automatic signature generation association mining hierarchical clustering LW_ DPI
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