/// <summary>Compute similarity between one item and a collection of items</summary>
/// <param name="item_id">the item ID</param>
/// <param name="items">a collection of items</param>
/// <param name="item_correlation">the similarity measure to use</param>
/// <returns>the similarity between the item and the collection</returns>
public static float Similarity(int item_id, ICollection<int> items, SymmetricCorrelationMatrix item_correlation)
{
double similarity = 0;
foreach (int other_item_id in items)
similarity += item_correlation[item_id, other_item_id];
return (float) similarity;
}
public void TestReadCorrelationMatrix()
{
// create test object
const string filename = "correlation_matrix.txt";
var writer = new StreamWriter(filename);
writer.WriteLine(3);
writer.WriteLine("0 1 0.1");
writer.WriteLine("0 2 0.2");
writer.WriteLine("1 2 0.3");
writer.Close();
var reader = new StreamReader(filename);
var corr_matrix = new SymmetricCorrelationMatrix(0);
corr_matrix.ReadSymmetricCorrelationMatrix(reader);
Assert.AreEqual(1f, corr_matrix[0, 0]);
Assert.AreEqual(1f, corr_matrix[1, 1]);
Assert.AreEqual(1f, corr_matrix[2, 2]);
Assert.AreEqual(0.1f, corr_matrix[0, 1]);
Assert.AreEqual(0.1f, corr_matrix[1, 0]);
Assert.AreEqual(0.2f, corr_matrix[0, 2]);
Assert.AreEqual(0.2f, corr_matrix[2, 0]);
Assert.AreEqual(0.3f, corr_matrix[1, 2]);
Assert.AreEqual(0.3f, corr_matrix[2, 1]);
// TODO test Exception
// test with wrong format
// close streams an delete the text file
reader.Close();
//File.Delete(filename);
}
public void TestGetPositivelyCorrelatedEntities()
{
// create a test CorrelationMatrix
var matrix = new SymmetricCorrelationMatrix(3);
matrix[0, 0] = 1f;
matrix[0, 1] = 0.1f;
matrix[0, 2] = -0.2f;
matrix[1, 0] = 0.1f;
matrix[1, 1] = 1f;
matrix[1, 2] = 0.3f;
matrix[2, 0] = -0.2f;
matrix[2, 1] = 0.3f;
matrix[2, 2] = 1f;
Assert.AreEqual(1f, matrix[0, 0]);
Assert.AreEqual(0.3f, matrix[1, 2]);
// test
IList <int> cor_entities_list = matrix.GetPositivelyCorrelatedEntities(2);
int[] cor_entities = new int[1];
cor_entities_list.CopyTo(cor_entities, 0);
int[] pos_cor_entities = { 1 };
Assert.AreEqual(pos_cor_entities, cor_entities);
}
///
public override void LearnAttributeToFactorMapping()
{
BinaryCosine cosine_correlation = new BinaryCosine(MaxItemID + 1);
Console.Error.WriteLine("training with max_item_id={0}", MaxItemID);
cosine_correlation.ComputeCorrelations(item_attributes);
this.item_correlation = cosine_correlation;
_MapToLatentFactorSpace = Utils.Memoize<int, float[]>(__MapToLatentFactorSpace);
}
///
public override void LearnAttributeToFactorMapping()
{
BinaryCosine cosine_correlation = new BinaryCosine(MaxItemID + 1);
Console.Error.WriteLine("training with max_item_id={0}", MaxItemID);
cosine_correlation.ComputeCorrelations(item_attributes);
this.item_correlation = cosine_correlation;
_MapToLatentFactorSpace = Utils.Memoize <int, float[]>(__MapToLatentFactorSpace);
}
/// <summary>Compute similarity between one item and a collection of items</summary>
/// <param name="item_id">the item ID</param>
/// <param name="items">a collection of items</param>
/// <param name="item_correlation">the similarity measure to use</param>
/// <returns>the similarity between the item and the collection</returns>
public static float Similarity(int item_id, ICollection <int> items, SymmetricCorrelationMatrix item_correlation)
{
double similarity = 0;
foreach (int other_item_id in items)
{
similarity += item_correlation[item_id, other_item_id];
}
return((float)similarity);
}
public void TestWrite()
{
// create a test CorrelationMatrix
var matrix = new SymmetricCorrelationMatrix(3);
matrix[0, 0] = 1f;
matrix[0, 1] = 0.1f;
matrix[0, 2] = 0.2f;
matrix[1, 0] = 0.1f;
matrix[1, 1] = 1f;
matrix[1, 2] = 0.3f;
matrix[2, 0] = 0.2f;
matrix[2, 1] = 0.3f;
matrix[2, 2] = 1f;
// test
string filename = "testCorrelationMatrixWriter.txt";
var writer = new StreamWriter(filename);
matrix.Write(writer);
writer.Close();
// check file format
var reader1 = new StreamReader(filename);
Assert.AreEqual("3", reader1.ReadLine().Trim());
Assert.AreEqual("0 1 0.1", reader1.ReadLine().Trim());
Assert.AreEqual("0 2 0.2", reader1.ReadLine().Trim());
Assert.AreEqual("1 2 0.3", reader1.ReadLine().Trim());
reader1.Close();
// check result of reading in the file
var reader2 = new StreamReader(filename);
var corr_matrix = new SymmetricCorrelationMatrix(0);
corr_matrix.ReadSymmetricCorrelationMatrix(reader2);
Assert.AreEqual(1f, corr_matrix[0, 0]);
Assert.AreEqual(0.1f, corr_matrix[0, 1]);
Assert.AreEqual(0.2f, corr_matrix[0, 2]);
Assert.AreEqual(0.1f, corr_matrix[1, 0]);
Assert.AreEqual(1f, corr_matrix[1, 1]);
Assert.AreEqual(0.3f, corr_matrix[1, 2]);
Assert.AreEqual(0.2f, corr_matrix[2, 0]);
Assert.AreEqual(0.3f, corr_matrix[2, 1]);
Assert.AreEqual(1f, corr_matrix[2, 2]);
reader2.Close();
// clean up
File.Delete(filename);
}
/// <summary>Compute the intra-set similarity of an item collection</summary>
/// <param name="items">a collection of items</param>
/// <param name="item_correlation">the similarity measure to use</param>
/// <returns>the intra-set similarity of the collection</returns>
public static float Similarity(ICollection <int> items, SymmetricCorrelationMatrix item_correlation)
{
double similarity = 0;
for (int i = 0; i < items.Count; i++)
{
for (int j = i + 1; j < items.Count; j++)
{
similarity += item_correlation[i, j];
}
}
return((float)similarity);
}
public void TestWrite()
{
// create a test CorrelationMatrix
var matrix = new SymmetricCorrelationMatrix(3);
matrix[0, 0] = 1f;
matrix[0, 1] = 0.1f;
matrix[0, 2] = 0.2f;
matrix[1, 0] = 0.1f;
matrix[1, 1] = 1f;
matrix[1, 2] = 0.3f;
matrix[2, 0] = 0.2f;
matrix[2, 1] = 0.3f;
matrix[2, 2] = 1f;
// test
string filename = "testCorrelationMatrixWriter.txt";
var writer = new StreamWriter(filename);
matrix.Write(writer);
writer.Close();
// check file format
var reader1 = new StreamReader(filename);
Assert.AreEqual("3", reader1.ReadLine().Trim());
Assert.AreEqual("0 1 0.1", reader1.ReadLine().Trim());
Assert.AreEqual("0 2 0.2", reader1.ReadLine().Trim());
Assert.AreEqual("1 2 0.3", reader1.ReadLine().Trim());
reader1.Close();
// check result of reading in the file
var reader2 = new StreamReader(filename);
var corr_matrix = new SymmetricCorrelationMatrix(0);
corr_matrix.ReadSymmetricCorrelationMatrix(reader2);
Assert.AreEqual(1f, corr_matrix[0, 0]);
Assert.AreEqual(0.1f, corr_matrix[0, 1]);
Assert.AreEqual(0.2f, corr_matrix[0, 2]);
Assert.AreEqual(0.1f, corr_matrix[1, 0]);
Assert.AreEqual(1f, corr_matrix[1, 1]);
Assert.AreEqual(0.3f, corr_matrix[1, 2]);
Assert.AreEqual(0.2f, corr_matrix[2, 0]);
Assert.AreEqual(0.3f, corr_matrix[2, 1]);
Assert.AreEqual(1f, corr_matrix[2, 2]);
reader2.Close();
// clean up
File.Delete(filename);
}
public void TestAddEntity()
{
// create a test CorrelationMatrix
var matrix = new SymmetricCorrelationMatrix(3);
matrix[0, 0] = 1f;
matrix[0, 2] = 0.2f;
matrix[1, 1] = 1f;
matrix[1, 2] = 0.3f;
matrix[2, 1] = 0.3f;
matrix[2, 2] = 1f;
// test
Assert.AreEqual(3, matrix.NumberOfRows);
matrix.AddEntity(3);
Assert.AreEqual(4, matrix.NumberOfRows);
}
public void TestSumUp()
{
// create a test CorrelationMatrix
var matrix = new SymmetricCorrelationMatrix(3);
matrix[0, 0] = 1f;
matrix[0, 1] = 0.1f;
matrix[0, 2] = 0.2f;
matrix[1, 0] = 0.1f;
matrix[1, 1] = 1f;
matrix[1, 2] = 0.3f;
matrix[2, 0] = 0.2f;
matrix[2, 1] = 0.3f;
matrix[2, 2] = 1f;
// test
Assert.AreEqual(0.3f, matrix.SumUp(0, new int[] { 1, 2 }), 0.00001);
}
public void TestGetNearestNeighbors()
{
// create a test CorrelationMatrix
var matrix = new SymmetricCorrelationMatrix(3);
matrix[0, 0] = 1f;
matrix[0, 1] = 0.1f;
matrix[0, 2] = 0.2f;
matrix[1, 0] = 0.1f;
matrix[1, 1] = 1f;
matrix[1, 2] = 0.3f;
matrix[2, 0] = 0.2f;
matrix[2, 1] = 0.3f;
matrix[2, 2] = 1f;
// test
IList <int> nn_test = matrix.GetNearestNeighbors(2, 2);
IList <int> nn_sol = new int[] { 1, 0 };
Assert.AreEqual(nn_sol, nn_test);
}
public void TestReadCorrelationMatrix()
{
// create test object
const string filename = "correlation_matrix.txt";
var writer = new StreamWriter(filename);
writer.WriteLine(3);
writer.WriteLine("0 1 0.1");
writer.WriteLine("0 2 0.2");
writer.WriteLine("1 2 0.3");
writer.Close();
var reader = new StreamReader(filename);
var corr_matrix = new SymmetricCorrelationMatrix(0);
corr_matrix.ReadSymmetricCorrelationMatrix(reader);
Assert.AreEqual(1f, corr_matrix[0, 0]);
Assert.AreEqual(1f, corr_matrix[1, 1]);
Assert.AreEqual(1f, corr_matrix[2, 2]);
Assert.AreEqual(0.1f, corr_matrix[0, 1]);
Assert.AreEqual(0.1f, corr_matrix[1, 0]);
Assert.AreEqual(0.2f, corr_matrix[0, 2]);
Assert.AreEqual(0.2f, corr_matrix[2, 0]);
Assert.AreEqual(0.3f, corr_matrix[1, 2]);
Assert.AreEqual(0.3f, corr_matrix[2, 1]);
// TODO test Exception
// test with wrong format
// close streams an delete the text file
reader.Close();
//File.Delete(filename);
}
/// <summary>Constructor</summary>
/// <param name="item_correlation">the similarity measure to use for diversification</param>
public SequentialDiversification(SymmetricCorrelationMatrix item_correlation)
{
ItemCorrelations = item_correlation;
}
public void TestGetNearestNeighbors()
{
// create a test CorrelationMatrix
var matrix = new SymmetricCorrelationMatrix(3);
matrix[0, 0] = 1f;
matrix[0, 1] = 0.1f;
matrix[0, 2] = 0.2f;
matrix[1, 0] = 0.1f;
matrix[1, 1] = 1f;
matrix[1, 2] = 0.3f;
matrix[2, 0] = 0.2f;
matrix[2, 1] = 0.3f;
matrix[2, 2] = 1f;
// test
IList<int> nn_test = matrix.GetNearestNeighbors(2, 2);
IList<int> nn_sol = new int[]{ 1, 0 };
Assert.AreEqual(nn_sol, nn_test);
}
public void TestGetPositivelyCorrelatedEntities()
{
// create a test CorrelationMatrix
var matrix = new SymmetricCorrelationMatrix(3);
matrix[0, 0] = 1f;
matrix[0, 1] = 0.1f;
matrix[0, 2] = -0.2f;
matrix[1, 0] = 0.1f;
matrix[1, 1] = 1f;
matrix[1, 2] = 0.3f;
matrix[2, 0] = -0.2f;
matrix[2, 1] = 0.3f;
matrix[2, 2] = 1f;
Assert.AreEqual(1f, matrix[0, 0]);
Assert.AreEqual(0.3f, matrix[1, 2]);
// test
IList<int> cor_entities_list = matrix.GetPositivelyCorrelatedEntities(2);
int[] cor_entities = new int[1];
cor_entities_list.CopyTo(cor_entities, 0);
int[] pos_cor_entities = { 1 };
Assert.AreEqual(pos_cor_entities, cor_entities);
}
public void TestSumUp()
{
// create a test CorrelationMatrix
var matrix = new SymmetricCorrelationMatrix(3);
matrix[0, 0] = 1f;
matrix[0, 1] = 0.1f;
matrix[0, 2] = 0.2f;
matrix[1, 0] = 0.1f;
matrix[1, 1] = 1f;
matrix[1, 2] = 0.3f;
matrix[2, 0] = 0.2f;
matrix[2, 1] = 0.3f;
matrix[2, 2] = 1f;
// test
Assert.AreEqual(0.3f, matrix.SumUp(0, new int[] {1, 2}), 0.00001);
}
public void TestAddEntity()
{
// create a test CorrelationMatrix
var matrix = new SymmetricCorrelationMatrix(3);
matrix[0, 0] = 1f;
matrix[0, 2] = 0.2f;
matrix[1, 1] = 1f;
matrix[1, 2] = 0.3f;
matrix[2, 1] = 0.3f;
matrix[2, 2] = 1f;
// test
Assert.AreEqual(3, matrix.NumberOfRows);
matrix.AddEntity(3);
Assert.AreEqual(4, matrix.NumberOfRows);
}
/// <summary>Compute the intra-set similarity of an item collection</summary>
/// <param name="items">a collection of items</param>
/// <param name="item_correlation">the similarity measure to use</param>
/// <returns>the intra-set similarity of the collection</returns>
public static float Similarity(ICollection<int> items, SymmetricCorrelationMatrix item_correlation)
{
double similarity = 0;
for (int i = 0; i < items.Count; i++)
for (int j = i + 1; j < items.Count; j++)
similarity += item_correlation[i, j];
return (float) similarity;
}
/// <summary>Constructor</summary>
/// <param name="item_correlation">the similarity measure to use for diversification</param>
public SequentialDiversification(SymmetricCorrelationMatrix item_correlation)
{
ItemCorrelations = item_correlation;
}
