//---------------------------------------------------------------------------------------
//This function computes the Confident Matrix and Weight Matrix, forllowing the formulars
//---------------------------------------------------------------------------------------
public void ComputeConfident(Predict_DAO_MCol dao)
{
dao.CLEAN_CONF_Matrix();
dao.CLEAN_WEIG_Matrix();
List<string> list_ClusterID = dao.getAllClusterID();
foreach (var item in list_ClusterID)
{
List<Transac> u_transacs = dao.getTransac_ForMatrix_ByClusterID_V2(item);
if (u_transacs.Count > 0)
{
// Get QuantityMatrix - MC
Dictionary<string, int> QM_dic_users = new Dictionary<string, int>();
Dictionary<string, int> QM_dic_items = new Dictionary<string, int>();
double[][] QuantityMatrix = Util.getQuantityMatrix_FromTransac_ByMetaItemID(u_transacs, out QM_dic_users, out QM_dic_items);
if (QuantityMatrix[0].Length > 1)
{
// Compute Support One Item Matrix - MC
double[] S = new double[QuantityMatrix[0].Length];
for (int j = 0; j < QuantityMatrix[0].Length; j++)
{
double count = 0.0;
for (int i = 0; i < QuantityMatrix.Length; i++)
if (QuantityMatrix[i][j] > 0)
count++;
S[j] = count;
}
// Compute Support Matrix - MC
double[][] SupportMatrix = new double[QuantityMatrix[0].Length][];
for (int i = 0; i < QuantityMatrix[0].Length; i++)
SupportMatrix[i] = new double[QuantityMatrix[0].Length];
for (int i = 0; i < QuantityMatrix.Length; i++)
{
for (int j = 0; j < QuantityMatrix[0].Length; j++)
for (int j2 = 0; j2 < QuantityMatrix[0].Length; j2++)
if (QuantityMatrix[i][j] > 0 & QuantityMatrix[i][j2] > 0 & j != j2)
SupportMatrix[j][j2]++;
}
// Compute CONF Matrix - MC
double[][] CONF = new double[QuantityMatrix[0].Length][];
for (int i = 0; i < QuantityMatrix[0].Length; i++)
CONF[i] = new double[QuantityMatrix[0].Length];
for (int i = 0; i < QuantityMatrix[0].Length; i++)
{
for (int j = 0; j < QuantityMatrix[0].Length; j++)
if (i == j)
CONF[i][j] = 1.0;
else if (S[i] > 0)
CONF[i][j] = SupportMatrix[i][j] / S[i];
}
// Compute WEIG Matrix - MC
double[][] WEIG = new double[QuantityMatrix[0].Length][];
for (int i = 0; i < QuantityMatrix[0].Length; i++)
WEIG[i] = new double[QuantityMatrix[0].Length];
for (int i = 0; i < QuantityMatrix[0].Length; i++)
{
for (int j = 0; j < QuantityMatrix[0].Length; j++)
if (i != j)
WEIG[i][j] = computeWEIG(i, j, SupportMatrix, QuantityMatrix);
}
// Save CONF Matrix - MC
for (int i = 0; i < CONF.Length; i++)
for (int j = 0; j < CONF[0].Length; j++)
if (CONF[i][j] > 0)
{
MatrixItem matrixItem = new MatrixItem();
matrixItem.Row = Util.FindKeyByValue(QM_dic_items, i);
matrixItem.Column = Util.FindKeyByValue(QM_dic_items, j);
matrixItem.Cell = CONF[i][j];
matrixItem.ClusterID = item;
dao.setCONF_Matrix(matrixItem);
}
// Save WEIG Matrix
for (int i = 0; i < WEIG.Length; i++)
for (int j = 0; j < WEIG[0].Length; j++)
if (WEIG[i][j] > 0)
{
MatrixItem matrixItem = new MatrixItem();
matrixItem.Row = Util.FindKeyByValue(QM_dic_items, i);
matrixItem.Column = Util.FindKeyByValue(QM_dic_items, j);
matrixItem.Cell = WEIG[i][j];
matrixItem.ClusterID = item;
dao.setWEIG_Matrix(matrixItem);
}
}
}
}
}
//---------------------------------------------------------------------------------------
//This function computes the DISTANCE matrix and inserts it into the database
//This is the distance between the two columns of the Rating Matrix
//---------------------------------------------------------------------------------------
public void ComputeDIST(Predict_DAO_MCol dao)
{
//dao.CLEAN_DIST_Matrix();
List<string> list_ClusterID = dao.getAllClusterID();
foreach (var item in list_ClusterID)
{
Dictionary<string, int> RM_dic_users = new Dictionary<string, int>();
Dictionary<string, int> RM_dic_items = new Dictionary<string, int>();
// Compute ratting matrix
List<MatrixItem> lstRMI = dao.getRattingMatrixItem_ByClusterID(item);
double[][] RattingMatrix = Util.toMatrix_MatrixItem(lstRMI, out RM_dic_users, out RM_dic_items);
if (RattingMatrix.Length > 0 & RM_dic_items.Count > 1)
{
double[][] DIST = new double[RattingMatrix[0].Length][];
for (int i = 0; i < RattingMatrix[0].Length; i++)
DIST[i] = new double[RattingMatrix[0].Length];
// Compute DIST Matrix
for (int i1 = 0; i1 < RattingMatrix[0].Length - 1; i1++)
for (int i2 = i1 + 1; i2 < RattingMatrix[0].Length; i2++)
{
double value = 0.0;
for (int t = 0; t < RattingMatrix.Length; t++)
value += Math.Pow(RattingMatrix[t][i1] - RattingMatrix[t][i2], 2);
value = Math.Sqrt(value);
DIST[i1][i2] = value;
DIST[i2][i1] = value;
}
if (DIST.Length > 0)
{
double max = DIST[0][0];
// Find Max
for (int i = 0; i < DIST.Length; i++)
{
double localMax = DIST[i].Max();
if (localMax > max)
max = localMax;
}
// Standardization
if (max != 0)
{
for (int i = 0; i < DIST.Length; i++)
for (int j = 0; j < DIST[0].Length; j++)
DIST[i][j] /= max;
}
// Save to Database
for (int i = 0; i < DIST.Length; i++)
for (int j = 0; j < DIST[0].Length; j++)
if (DIST[i][j] > 0)
{
MatrixItem matrixItem = new MatrixItem();
matrixItem.Row = Util.FindKeyByValue(RM_dic_items, i);
matrixItem.Column = Util.FindKeyByValue(RM_dic_items, j);
matrixItem.Cell = DIST[i][j];
matrixItem.ClusterID = item;
dao.setDIST_Matrix(matrixItem);
}
}
}
}
}