In this paper,the problem of increasing information transfer authenticity is formulated.And to reach a decision,the control methods and algorithms based on the use of statistical and structural information redundancy ...In this paper,the problem of increasing information transfer authenticity is formulated.And to reach a decision,the control methods and algorithms based on the use of statistical and structural information redundancy are presented.It is assumed that the controllable information is submitted as the text element images and it contains redundancy,caused by statistical relations and non-uniformity probability distribution of the transmitted data.The use of statistical redundancy allows to develop the adaptive rules of the authenticity control which take into account non-stationarity properties of image data while transferring the information.The structural redundancy peculiar to the container of image in a data transfer package is used for developing new rules to control the information authenticity on the basis of pattern recognition mechanisms.The techniques offered in this work are used to estimate the authenticity in structure of data transfer packages.The results of comparative analysis for developed methods and algorithms show that their parameters of efficiency are increased by criterion of probability of undetected mistakes,labour input and cost of realization.展开更多
为了提高文本聚类的性能,采用k-modes算法进行文本聚类,并采用知识图谱进行样本预分析,以提高k-modes的文本聚类适用度。采用知识图谱进行样本预处理,对待聚类的文本进行知识图谱三元分析,并生成对应概念、实体和关系的样本集合;接着建...为了提高文本聚类的性能,采用k-modes算法进行文本聚类,并采用知识图谱进行样本预分析,以提高k-modes的文本聚类适用度。采用知识图谱进行样本预处理,对待聚类的文本进行知识图谱三元分析,并生成对应概念、实体和关系的样本集合;接着建立k-modes文本聚类模型,设定簇内节点至簇中心的距离值之和为目标函数,通过轮流固定隶属矩阵和聚类簇矩阵,不断求解目标函数的最小值直至目标函数值稳定,获得簇中心,最后根据簇中心及各节点到簇中心距离来确定聚类结果。实验表明,经过知识图谱分析之后,k-modes算法能够获得更优的纯度、标准互信息和F值性能,且聚类纯度的均方根误差(Root mean squared error,RMSE)值更低;和常用文本聚类算法相比,对于UCI集和新闻集,该文算法均表现出了更高的聚类准确率。展开更多
文摘In this paper,the problem of increasing information transfer authenticity is formulated.And to reach a decision,the control methods and algorithms based on the use of statistical and structural information redundancy are presented.It is assumed that the controllable information is submitted as the text element images and it contains redundancy,caused by statistical relations and non-uniformity probability distribution of the transmitted data.The use of statistical redundancy allows to develop the adaptive rules of the authenticity control which take into account non-stationarity properties of image data while transferring the information.The structural redundancy peculiar to the container of image in a data transfer package is used for developing new rules to control the information authenticity on the basis of pattern recognition mechanisms.The techniques offered in this work are used to estimate the authenticity in structure of data transfer packages.The results of comparative analysis for developed methods and algorithms show that their parameters of efficiency are increased by criterion of probability of undetected mistakes,labour input and cost of realization.
文摘为了提高文本聚类的性能,采用k-modes算法进行文本聚类,并采用知识图谱进行样本预分析,以提高k-modes的文本聚类适用度。采用知识图谱进行样本预处理,对待聚类的文本进行知识图谱三元分析,并生成对应概念、实体和关系的样本集合;接着建立k-modes文本聚类模型,设定簇内节点至簇中心的距离值之和为目标函数,通过轮流固定隶属矩阵和聚类簇矩阵,不断求解目标函数的最小值直至目标函数值稳定,获得簇中心,最后根据簇中心及各节点到簇中心距离来确定聚类结果。实验表明,经过知识图谱分析之后,k-modes算法能够获得更优的纯度、标准互信息和F值性能,且聚类纯度的均方根误差(Root mean squared error,RMSE)值更低;和常用文本聚类算法相比,对于UCI集和新闻集,该文算法均表现出了更高的聚类准确率。
