【摘要】 软件胎记选择关系着软件的识别率.本文应用约束聚类分析软件特征,基于互信息度量特征的类内和类间距离,以同类和异类软件特征构建信息增益函数和惩罚函数,选择出具有高的类区分信息和最小冗余的软件胎记特征.通过分析和比较表明该算法为软件胎记特征的选择和优化提供了一种有效途径.更多还原

【Abstract】 The feature selection for sof tware birthmark has a direct bearing on sof tware recognition rate.We apply constrained clustering to analyze sof tware features.The within-and between-class distances of features are measured based on mutual information.Information gain and penalty functions are constructed using homogeneous and heterogeneous sof tware features respectively.Then the sof tware birthmark features with high class distinction and minimum redundancy are selected.It is shown the algorithm provide an effective approach for sof tware birthmark feature selection and optimization by analysis and comparison.更多还原