public Dictionary <string, double> CalculateSimilarity(TermDocumentMatrixModel documentMatrix, string query)
{
Dictionary <string, int> isTermInQuery = CountFrequencyOfTermQuery(query);
Dictionary <string, double> tfOfQuery = new Dictionary <string, double>();
Dictionary <string, double> idfOfQuery = new Dictionary <string, double>();
Dictionary <string, double> tf_idfOfQuery = new Dictionary <string, double>();
double vectorNorm = 0.0;
//tf of query , idf of query , tf_idf of query , vectorNorm
foreach (var item in isTermInQuery)
{
int numberOfTermInDocument = 0;
tfOfQuery.Add(item.Key, new TermDocumentMatrix().CalculateTF(item.Value));
if (documentMatrix.IsTermInDocument.ContainsKey(item.Key))
{
numberOfTermInDocument = documentMatrix.IsTermInDocument[item.Key];
}
idfOfQuery.Add(item.Key, new TermDocumentMatrix().CalculateIDF(numberOfTermInDocument, documentMatrix.DocumentList.Count()));
tf_idfOfQuery.Add(item.Key, new TermDocumentMatrix().CalculateTF_IDF(tfOfQuery[item.Key], idfOfQuery[item.Key]));
vectorNorm = vectorNorm + Math.Pow(tf_idfOfQuery[item.Key], 2);
}
vectorNorm = Math.Round(Math.Sqrt(vectorNorm), 3);
//cosine similarity
var result = CalcaulateCosineSimilarity(tf_idfOfQuery, vectorNorm, documentMatrix);
return(result);
}
public TermDocumentMatrixModel SettingTermDocumentMatrix(TermDocumentMatrixModel documentMatrix)
{
Dictionary <string, int> IsTermInDocument = new Dictionary <string, int>();
Dictionary <string, Dictionary <string, double> > TFIndexTermOfDocumentList = new Dictionary <string, Dictionary <string, double> >();
Dictionary <string, double> IDFIndexTermOfDocument = new Dictionary <string, double>();
Dictionary <string, Dictionary <string, double> > TF_IDFIndexTermOfDocumentList = new Dictionary <string, Dictionary <string, double> >();
//Term all
foreach (var item in documentMatrix.IndexTermList)
{
int countTermInDocument = 0;
Dictionary <string, double> TFIndexTermOfDocument = new Dictionary <string, double>();
Dictionary <string, double> TF_IDFIndexTermOfDocument = new Dictionary <string, double>();
//document
foreach (var indexdocterm in documentMatrix.DocumentList)
{
//Ni
if (indexdocterm.IndexTermDocuments.ContainsKey(item))
{
countTermInDocument++;
//Calculate TF
TFIndexTermOfDocument.Add(indexdocterm.Name, CalculateTF(indexdocterm.IndexTermDocuments[item]));
}
else
{
//TF = 0
TFIndexTermOfDocument.Add(indexdocterm.Name, 0);
}
}
//Calculate IDF
IDFIndexTermOfDocument.Add(item, CalculateIDF(countTermInDocument, documentMatrix.DocumentList.Count()));
IsTermInDocument.Add(item, countTermInDocument);
TFIndexTermOfDocumentList.Add(item, TFIndexTermOfDocument);
foreach (var document in documentMatrix.DocumentList)
{
//calulate IF_IDF
var tfOfDocumentList = TFIndexTermOfDocumentList[item];
var result = CalculateTF_IDF(tfOfDocumentList[document.Name], IDFIndexTermOfDocument[item]);
TF_IDFIndexTermOfDocument.Add(document.Name, result);
document.VectorNorm = document.VectorNorm + Math.Pow(result, 2);
}
TF_IDFIndexTermOfDocumentList.Add(item, TF_IDFIndexTermOfDocument);
}
//VectorNorm
foreach (var document in documentMatrix.DocumentList)
{
document.VectorNorm = Math.Round(Math.Sqrt(document.VectorNorm), 3);
}
documentMatrix.IDFIndexTermOfDocument = IDFIndexTermOfDocument;
documentMatrix.TFIndexTermOfDocument = TFIndexTermOfDocumentList;
documentMatrix.IsTermInDocument = IsTermInDocument;
documentMatrix.TF_IDFIndexTermOfDocument = TF_IDFIndexTermOfDocumentList;
return(documentMatrix);
}
public void DisplayHead(TermDocumentMatrixModel documentMatrixModel)
{
Console.WriteLine("==[ Vector Model ]==");
Console.WriteLine(string.Format("\nInformation: We use these {0} articles from Medium.com for demonstrating the Vector Model", documentMatrixModel.DocumentList.Count));
for (int i = 0; i < documentMatrixModel.DocumentList.Count; i++)
{
Console.WriteLine(string.Format("({0}) {1}", i + 1, documentMatrixModel.DocumentList[i].Name));
}
Console.WriteLine("The result will show the retrieved document and similarity of Vector Model");
Console.WriteLine("\n------------------------------\n");
}
public void DisplayBodyResult(TermDocumentMatrixModel documentMatrixModel, Dictionary <string, double> cosineSimilarity, string query)
{
Console.WriteLine("\n\n=[ Similarity ]=\n");
Console.WriteLine("Query is :{0}", query);
ConsoleTableBuilder.From(GetSampleTableData(cosineSimilarity)).ExportAndWriteLine();
}
public Dictionary <string, double> CalcaulateCosineSimilarity(Dictionary <string, double> tf_idfQuery, double vectorNorm, TermDocumentMatrixModel documentMatrix)
{
Dictionary <string, double> cosineSimilarity = new Dictionary <string, double>();
foreach (var item in documentMatrix.DocumentList)
{
//follow by document
double crossWeight = 0.0;
double crossSumVectorNorm = 0.0;
double cosineSimilarityOfDocument = 0.0;
foreach (var tf_idfQItem in tf_idfQuery)
{
if (documentMatrix.TF_IDFIndexTermOfDocument.ContainsKey(tf_idfQItem.Key))
{
var tF_IDFList = documentMatrix.TF_IDFIndexTermOfDocument[tf_idfQItem.Key];
crossWeight = crossWeight + (tF_IDFList[item.Name] * tf_idfQItem.Value);
}
else
{
crossWeight = crossWeight + (0 * tf_idfQItem.Value);
}
}
crossSumVectorNorm = Math.Round(item.VectorNorm * vectorNorm, 3);
cosineSimilarityOfDocument = Math.Round(crossWeight / crossSumVectorNorm, 3);
cosineSimilarity.Add(item.Name, cosineSimilarityOfDocument);
}
return(cosineSimilarity);
}
