private void WriteRankingResult()
{
Dictionary <string, Dictionary <string, float> > topicDocDensity = new Dictionary <string, Dictionary <string, float> >();
foreach (string doc in docTopicDensityMap.Keys) //transfer the primaryKey from docId to topicId
{
Dictionary <string, float> topicDensity = docTopicDensityMap[doc];
foreach (string topicName in topicDensity.Keys)
{
float density = topicDensity[topicName];
if (topicDocDensity.ContainsKey(topicName))
{
topicDocDensity[topicName].Add(doc, density);
}
else
{
Dictionary <string, float> docDensity = new Dictionary <string, float>();
docDensity.Add(doc, density);
topicDocDensity.Add(topicName, docDensity);
}
}
}
foreach (string topicName in topicDocDensity.Keys)
{
Dictionary <string, float> relevantDocDensity = topicDocDensity[topicName];
Dictionary <string, float> sortedDocDensity = DictionaryDecreasedSort.DecreasedByValue(relevantDocDensity);
string docAndDensity = "";
foreach (string key in sortedDocDensity.Keys)
{
string fileName = key.Substring(filePathLength);
float freq = sortedDocDensity[key];
if (freq > 0)
{
docAndDensity += topicName + "\t" + fileName + "\t" + sortedDocDensity[key] + "\r\n";
}
}
FileOperators.FileAppend(rankResult, docAndDensity);
}
}
public void executeRank()
{
getAllTopicTerms(); //get topic and the related terms, and do the normalization
int txtDirLength = docsPath.Length;
foreach (KeyValuePair <string, Dictionary <string, float> > entry in normalizedTopicTerms)
{
string topicName = entry.Key; //just the topic ID
Dictionary <string, float> termAndValues = entry.Value;
List <string> terms = new List <string>(termAndValues.Keys);
List <float> queryVector = new List <float>(termAndValues.Values);
// topicName = topicName.Replace(" ", string.Empty);
tfidfStore = docsPath + "-ifidf\\" + topicName + ".csv";
//for each document, generate the ifidf according to the keyterms of topic
TFIDF tfidf = new TFIDF(terms, this.docsPath, tfidfStore);
tfidf.calTfidf();
string[] tfidfLines = FileOperators.ReadFileLines(tfidfStore);
int lineScale = tfidfLines.Length;
VSM vsm = new VSM();
string simContent = "";
Dictionary <string, double> docAndRelevance = new Dictionary <string, double>();
for (int i = 1; i < lineScale; i++)
{
string curLine = tfidfLines[i];
int firstComma = curLine.IndexOf(';');
string fileName = curLine.Substring(0, firstComma); //test if the length is right
string valueStr = curLine.Substring(firstComma + 1);
string[] valueTerms = valueStr.Split(';');
List <float> docVector = new List <float>();
foreach (string valueTerm in valueTerms)
{
float value = float.Parse(valueTerm);
docVector.Add(value);
}
double sim = vsm.calSimilarity(docVector, queryVector);
if (sim > 0)
{
docAndRelevance.Add(fileName, sim); //get the similarity between doc and topic
}
}
//execute decrease sorting on the docAndRelevance
Dictionary <string, double> sortedByRelevance = DictionaryDecreasedSort.DecreasedByValue(docAndRelevance);
foreach (string key in sortedByRelevance.Keys)
{
double similarity = sortedByRelevance[key];
string fileName = key.Substring(txtDirLength);
simContent += topicName + "\t" + fileName + "\t" + similarity + "\r\n";
}
FileOperators.FileAppend(simStorePath, simContent); //simStorePath should contain relativePath
}
Console.WriteLine("DONE!!");
}
