/// <summary>
/// 计算所有用户的兴趣程度矩阵
/// </summary>
public void GetUserInterestMatrix()
{
Array.Clear(UserInterestMatrix, 0, itemTotal * userTotal);
for (int i = 0; i < userTotal; i++)
{
DataTable Tb_UserInterest = new DataTable();
Tb_UserInterest.Columns.Add("userID", System.Type.GetType("System.Int32"));
Tb_UserInterest.Columns.Add("itemID", System.Type.GetType("System.Int32"));
Tb_UserInterest.Columns.Add("interest", System.Type.GetType("System.Double"));
string tableName = "UserInterest";
for (int j = 0; j < itemTotal; j++)
{
if (TrainSet[j, i] == 0)
{
UserInterestMatrix[i, j] = CalculateUserInterest(i, j, 10);
DataRow row = Tb_UserInterest.NewRow();
row[0] = i + 1;
row[1] = j + 1;
row[2] = UserInterestMatrix[i, j];
Tb_UserInterest.Rows.Add(row);
}
}
SqlSeverProvider.ExecuteSqlBulkCopy(Tb_UserInterest, tableName);
}
}
/// <summary>
/// 推荐物品
/// </summary>
public void GetRecommend()
{
int mostInterestNum; //当前最感兴趣物品
for (int i = 0; i < userTotal; i++)
{
int [] orderFlag = new int[itemTotal];
for (int j = 0; j < recommendNum; j++)
{
mostInterestNum = 0;
while (orderFlag[mostInterestNum] != 0)
{
mostInterestNum++;
}
for (int k = 0; k < itemTotal; k++)
{
if (UserInterestMatrix[i, mostInterestNum] < UserInterestMatrix[j, k] && orderFlag[k] == 0)
{
mostInterestNum = k;
}
}
orderFlag[mostInterestNum] = 1;
RecommendSet[i, j] = mostInterestNum;
}
}
Console.WriteLine("推荐完成...");
for (int i = 0; i < 6040; i++)
{
DataTable Tb_Recommended = new DataTable();
Tb_Recommended.Columns.Add("userID", System.Type.GetType("System.Int32"));
Tb_Recommended.Columns.Add("itemID", System.Type.GetType("System.Int32"));
string tableName = "Recommended";
for (int j = 0; j < 10; j++)
{
var item = (int)RecommendSet[i, j];
//string str = string.Format("insert into Recommended values({0},{1})",i+1,item);
//SqlSeverProvider.ExecuteNonQuery(str);
DataRow row = Tb_Recommended.NewRow();
row[0] = i + 1;
row[1] = item;
Tb_Recommended.Rows.Add(row);
}
SqlSeverProvider.ExecuteSqlBulkCopy(Tb_Recommended, tableName);
}
Console.WriteLine("推荐完成22222...");
}
/// <summary>
/// 计算所有物品之间的相似性，得到相似性矩阵
/// </summary>
public void GetSimilarityMatrix()
{
Array.Clear(SimilarityMatrix, 0, itemTotal * itemTotal);
for (int i = 0; i < itemTotal; i++)
{
DataTable Tb_SimilarityMatrix = new DataTable();
Tb_SimilarityMatrix.Columns.Add("itemOne", System.Type.GetType("System.Int32"));
Tb_SimilarityMatrix.Columns.Add("itemTwo", System.Type.GetType("System.Int32"));
Tb_SimilarityMatrix.Columns.Add("similarity", System.Type.GetType("System.Double"));
string tableName = "SimilarityMatrix";
for (int j = 0; j < itemTotal; j++)
{
SimilarityMatrix[i, j] = CalculateSimilarityForA_B(i, j);
DataRow row = Tb_SimilarityMatrix.NewRow();
row[0] = i + 1;
row[1] = j + 1;
row[2] = SimilarityMatrix[i, j];
Tb_SimilarityMatrix.Rows.Add(row);
}
SqlSeverProvider.ExecuteSqlBulkCopy(Tb_SimilarityMatrix, tableName);
}
}