/// <summary>
/// Computes the cosine similarity between the given document pairs in the matrix
/// </summary>
/// <param name="matrix">Term-by-document matrix</param>
/// <param name="sourceIDs">Collection of source artifacts ids</param>
/// /// <param name="targetIDs">Collection of target artifacts ids</param>
/// <returns>Similarity matrix</returns>
public static TLSimilarityMatrix ComputeCosine(TermDocumentMatrix matrix, IEnumerable <string> sourceIDs, IEnumerable <string> targetIDs)
{
TLSimilarityMatrix sims = new TLSimilarityMatrix();
foreach (string sourceID in sourceIDs)
{
double[] sourceDoc = matrix.GetDocument(sourceID);
foreach (string targetID in targetIDs)
{
// compute cosine similarity between source and target
double[] targetDoc = matrix.GetDocument(targetID);
double lengthProduct = ComputeLength(sourceDoc) * ComputeLength(targetDoc);
if (lengthProduct == 0.0)
{
sims.AddLink(sourceID, targetID, 0.0);
}
else
{
double score = ComputeDotProduct(sourceDoc, targetDoc) / lengthProduct;
sims.AddLink(sourceID, targetID, score);
}
}
}
return(sims);
}
/// <summary>
/// Computes the term frequencies of each document.
/// Each term in a vector is divided by the max term in that vector.
/// </summary>
/// <param name="matrix">Term-by-document matrix</param>
/// <returns>tf-weighted term-by-document matrix</returns>
public static TermDocumentMatrix ComputeTF(TermDocumentMatrix matrix)
{
for (int i = 0; i < matrix.NumDocs; i++)
{
double max = matrix.GetDocument(i).Max();
for (int j = 0; j < matrix.NumTerms; j++)
{
matrix[i, j] = matrix[i, j] / max;
}
}
return(matrix);
}
public void ConstructorTest_Artifacts()
{
string data = @"../../Data/SimpleCorpus.";
TermDocumentMatrix matrix = new TermDocumentMatrix(Artifacts.Import(data + "input.target.txt"));
TermDocumentMatrix answer = TermDocumentMatrix.Load(data + "output.target.matrix.txt");
// counts
Assert.AreEqual(matrix.NumDocs, answer.NumDocs);
Assert.AreEqual(matrix.NumTerms, answer.NumTerms);
// matrix
for (int i = 0; i < answer.NumDocs; i++)
{
Assert.AreEqual(matrix.GetDocumentName(i), answer.GetDocumentName(i));
Assert.AreEqual(matrix.GetDocument(i).Length, answer.NumTerms);
for (int j = 0; j < answer.NumTerms; j++)
{
Assert.AreEqual(matrix.GetTermName(j), answer.GetTermName(j));
Assert.AreEqual(matrix[i, j], answer[i, j], 0.0);
}
}
}
public void ConstructorTest_Artifacts()
{
string inputData = Settings.Default.SimpleCorpusDir;
string outputData = Path.Combine(inputData, "TermDocumentMatrix");
TermDocumentMatrix matrix = new TermDocumentMatrix(Artifacts.ImportFile(Path.Combine(inputData, "target.txt")));
TermDocumentMatrix answer = TermDocumentMatrix.Load(Path.Combine(outputData, "output.txt"));
// counts
Assert.AreEqual(matrix.NumDocs, answer.NumDocs);
Assert.AreEqual(matrix.NumTerms, answer.NumTerms);
// matrix
for (int i = 0; i < answer.NumDocs; i++)
{
Assert.AreEqual(matrix.GetDocumentName(i), answer.GetDocumentName(i));
Assert.AreEqual(matrix.GetDocument(i).Length, answer.NumTerms);
for (int j = 0; j < answer.NumTerms; j++)
{
Assert.AreEqual(matrix.GetTermName(j), answer.GetTermName(j));
Assert.AreEqual(matrix[i, j], answer[i, j], 0.0);
}
}
}
/// <summary>
/// Computes the cosine similarity between the given document pairs in the matrix
/// </summary>
/// <param name="matrix">Term-by-document matrix</param>
/// <param name="sourceIDs">Collection of source artifacts ids</param>
/// /// <param name="targetIDs">Collection of target artifacts ids</param>
/// <returns>Similarity matrix</returns>
public static TLSimilarityMatrix ComputeCosine(TermDocumentMatrix matrix, IEnumerable<string> sourceIDs, IEnumerable<string> targetIDs)
{
TLSimilarityMatrix sims = new TLSimilarityMatrix();
foreach (string sourceID in sourceIDs)
{
double[] sourceDoc = matrix.GetDocument(sourceID);
foreach (string targetID in targetIDs)
{
// compute cosine similarity between source and target
double[] targetDoc = matrix.GetDocument(targetID);
double lengthProduct = ComputeLength(sourceDoc) * ComputeLength(targetDoc);
if (lengthProduct == 0.0)
{
sims.AddLink(sourceID, targetID, 0.0);
}
else
{
double score = ComputeDotProduct(sourceDoc, targetDoc) / lengthProduct;
sims.AddLink(sourceID, targetID, score);
}
}
}
return sims;
}
/// <summary>
/// Computes the term frequencies of each document.
/// Each term in a vector is divided by the max term in that vector.
/// </summary>
/// <param name="matrix">Term-by-document matrix</param>
/// <returns>tf-weighted term-by-document matrix</returns>
public static TermDocumentMatrix ComputeTF(TermDocumentMatrix matrix)
{
for (int i = 0; i < matrix.NumDocs; i++)
{
double max = matrix.GetDocument(i).Max();
for (int j = 0; j < matrix.NumTerms; j++)
{
matrix[i, j] = matrix[i, j] / max;
}
}
return matrix;
}