摘要
该文用"图"这一数学工具,通过定量分析来揭示语言系统中的隐性规律,设计了"赢家通吃"和"赢多输少"两种生成算法,将理想算法"步步竞争、择优而行"的博弈论思路贯彻到非理想状态。两种新算法都较前人有更好的概括能力。赢多输少算法更兼顾了充分概括和适度概括均衡。生成语图后,该设计着重准确率的最小简图和着重覆盖率的最大简图归纳算法,挖掘控制的主流规则、分析语言系统的语言学规律。在最小简图基础上提出控制度公式以评价语言系统。
We tried to reveal convert laws with quantitative analysis through graphs and designed two generating algorithms of language graphs： Winner-get-all and Winner-more-loser-less, which extend the game theory used by idea-algorithm to none-perfect state. Compared to previous methods, the proposed two algorithms have better generali zation capability. Especially, we balance between full and modest generation in the Winner-more loser less algo- rithm. There are two kinds of inductive algorithms to mine mainstream rules and analyze linguistic laws： Min-Subgraphs for accuracy, as well as Max-Subgraphs for coverage. A formula for control degree based on min-subgraphs is put forward to evaluate language systems.
出处
《中文信息学报》
CSCD
北大核心
2015年第5期20-30,共11页
Journal of Chinese Information Processing
基金
教育部人文社会科学规划基金"现代汉语句法与语义计算研究"(13YJA740005)
关键词
隐性规律
图论
博弈论
规则挖掘
covert laws
graph theory
game theory
rules mining
