我未能找到计算这一摘要的方法。
最近,我完成了一项LSA的实施工作,能够产生PPT的所有其它成果,但并非第25号。
我之所以要求这样做,是因为我要利用这一点来说明为什么文件得分高的原因。
我未能找到计算这一摘要的方法。
最近,我完成了一项LSA的实施工作,能够产生PPT的所有其它成果,但并非第25号。
我之所以要求这样做,是因为我要利用这一点来说明为什么文件得分高的原因。
Ok; I ve决定写上电点的作者(Dr. Melanie J Martin),她指出Deerseyer等人的论文第406页。
为了测试它,我举了一个例子,看看我是否能够获得同样的价值,我的工作是:
试验守则:
static void XHatTest()
{
double[,] testT = new double[12, 2], testD = new double[2, 9], testS = new double[2, 2];
testT[0, 0] = 0.22;
testT[0, 1] = -0.11;
testT[1, 0] = 0.20;
testT[1, 1] = -0.07;
testT[2, 0] = 0.24;
testT[2, 1] = 0.04;
testT[3, 0] = 0.40;
testT[3, 1] = 0.06;
testT[4, 0] = 0.64;
testT[4, 1] = -0.17;
testT[5, 0] = 0.27;
testT[5, 1] = 0.11;
testT[6, 0] = 0.27;
testT[6, 1] = 0.11;
testT[7, 0] = 0.30;
testT[7, 1] = -0.14;
testT[8, 0] = 0.21;
testT[8, 1] = 0.27;
testT[9, 0] = 0.01;
testT[9, 1] = 0.49;
testT[10, 0] = 0.04;
testT[10, 1] = 0.62;
testT[11, 0] = 0.03;
testT[11, 1] = 0.45;
testD[0, 0] = 0.20;
testD[0, 1] = 0.61;
testD[0, 2] = 0.46;
testD[0, 3] = 0.54;
testD[0, 4] = 0.28;
testD[0, 5] = 0.00;
testD[0, 6] = 0.02;
testD[0, 7] = 0.02;
testD[0, 8] = 0.08;
testD[1, 0] = -0.06;
testD[1, 1] = 0.17;
testD[1, 2] = -0.13;
testD[1, 3] = -0.23;
testD[1, 4] = 0.11;
testD[1, 5] = 0.19;
testD[1, 6] = 0.44;
testD[1, 7] = 0.62;
testD[1, 8] = 0.53;
testS[0, 0] = 3.34;
testS[0, 1] = 0;
testS[1, 0] = 0;
testS[1, 1] = 2.54;
Matrix A = new Matrix(testT), B = new Matrix(testD), C = new Matrix(testS);
Matrix Result = A * C * B;
for (int row = 0; row < Result.NoRows; row++)
{
for (int col = 0; col < Result.NoCols; col++)
{
Console.Write(Math.Round(Result[row, col], 2) + " ");
}
Console.WriteLine();
}
}
Is there a C++ library for LSA/LSI? Preferably MIT, BSD, Apache,... license - no GPL.
请查http://www.cs.nmsu.edu/~mmartin/LSA_Intro_AI_Seminar.ppt 这些数字显示了Slide25中每一字的计算分数。
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