private List <KeyValuePair <Document, double> > CalculateCosScores(List <string> tokens, DfWrapper wrapper)
{
List <KeyValuePair <int, double> > scores = new List <KeyValuePair <int, double> >();
foreach (Document doc in wrapper.DocumentList)
{
double tempVal = 0;
foreach (string word in tokens)
{
if (doc.TermFrequency != 0)
{
tempVal += (1 + Math.Log(doc.TermFrequency));
}
}
scores.Add(new KeyValuePair <int, double>(doc.Id, tempVal));
}
List <KeyValuePair <int, double> > length = new List <KeyValuePair <int, double> >();
foreach (Document item in wrapper.DocumentList)
{
double temp = 0;
foreach (string word in tokens)
{
if (incidenceVector[word].DocumentList.Contains(item))
{
temp += item.TfIdf * item.TfIdf;
}
}
length.Add(new KeyValuePair <int, double>(item.Id, Math.Sqrt(temp)));
}
List <KeyValuePair <int, double> > finalScores = new List <KeyValuePair <int, double> >();
foreach (KeyValuePair <int, double> item in scores)
{
double lengthVal = -1;
lengthVal = length.Find(x => x.Key == item.Key).Value;
if (lengthVal >= 0)
{
finalScores.Add(new KeyValuePair <int, double>(item.Key, item.Value / lengthVal));
}
}
finalScores = finalScores.OrderBy(x => x.Value).ToList();
List <KeyValuePair <Document, double> > finalDocumentPairs = new List <KeyValuePair <Document, double> >();
foreach (KeyValuePair <int, double> item in finalScores)
{
finalDocumentPairs.Add(new KeyValuePair <Document, double>(wrapper.DocumentList.Find(x => x.Id == item.Key), item.Value));
}
return(finalDocumentPairs);
}
public List <KeyValuePair <Document, double> > PassQuery(string inputQuery)
{
List <string> disectedQuery = new List <string>(inputQuery.ToLower().Split(' '));
disectedQuery.RemoveAll(e => stopWords.Exists(sw => sw.Equals(e)));
List <string> foundTokens = new List <string>();
List <Document> blacklistedDocuments = new List <Document>();
int queryTokenCounter = 0;
foreach (string queryWord in disectedQuery)
{
if (queryWord == "*not*")
{
if (queryTokenCounter != disectedQuery.Count)
{
blacklistedDocuments.AddRange(incidenceVector[disectedQuery[queryTokenCounter + 1]].DocumentList);
}
}
if (incidenceVector.ContainsKey(queryWord) && !foundTokens.Contains(queryWord))
{
foundTokens.Add(queryWord);
}
queryTokenCounter++;
}
DfWrapper foundPages = new DfWrapper();
//foundPages.DocumentList.AddRange(ANDpageFinder(foundTokens));
foundPages.DocumentList.AddRange(ORpageFinder(foundTokens));
foundPages.DocumentList = foundPages.DocumentList.Distinct().ToList();
foundPages.DocumentList.RemoveAll(e => blacklistedDocuments.Contains(e));
//foundPages.DocumentList.ForEach(e => Console.WriteLine(e.Id));
//REMEMBER 10 IS JUST CHOSEN RANDOMLY - Hardcode
CalculateTf_Idf(foundPages.DocumentList.Count);
List <KeyValuePair <Document, double> > cosscore = CalculateCosScores(foundTokens, foundPages);
double[] pageranks = _crawler.PageRanker(0.10, 200);
List <KeyValuePair <Document, double> > final = new List <KeyValuePair <Document, double> >();
for (int i = 0; i < pageranks.Length; i++)
{
KeyValuePair <Document, double> temp = cosscore.Find(x => x.Key.Id == i);
if (temp.Key != null)
{
final.Add(new KeyValuePair <Document, double>(temp.Key, pageranks[i] * temp.Value));
}
}
final.Sort((x, y) => x.Value.CompareTo(y.Value));
final.Reverse();
try
{
final = final.GetRange(0, 10);
}
catch (Exception)
{
}
return(final);
}
