protected void AddTerm(int docType, string doc, string term)
{
if (!TermFWByGlobal.ContainsKey(term))
{
TermFWByGlobal.Add(term, new TermFW(term));
}
if (!TermFWByType.ContainsKey(docType, term))
{
TermFWByType[docType].Add(term, new TermFW(term));
}
if (!TermFWByDoc.ContainsKey(docType, doc, term))
{
TermFWByDoc[docType][doc].Add(term, new TermFW(term));
}
TermFWByGlobal[term].Freq += 1;
TermFWByType[docType][term].Freq += 1;
TermFWByDoc[docType][doc][term].Freq += 1;
}
protected int GetDocTermsTrueCount(string doc1, string doc2)
{
var count = 0;
var terms1 = TermsByDoc[0, doc1];
var terms2 = TermsByDoc[1, doc2];
var terms = terms1.Union(terms2);
foreach (var term in terms)
{
if (TermFWByGlobal[term].Freq > 1)
{
if (TermFWByType.ContainsKey(0, term))
{
count += 1;
}
if (TermFWByType.ContainsKey(1, term))
{
count += 1;
}
}
}
return(count);
}
/// <summary>
/// 2文档中的相似度
/// </summary>
/// <param name="doc1"></param>
/// <param name="doc2"></param>
/// <returns></returns>
private double computerSimilar(string doc1, string doc2)
{
var terms1 = TermsByDoc[0, doc1];
var terms2 = TermsByDoc[1, doc2];
var terms = terms1.Union(terms2).ToArray();
//var tCount1 = TermsByDoc[0][doc1].Length;
//var tCount2 = TermsByDoc[1][doc2].Length;
double f, f1, f2;
f = 0; f1 = 0; f2 = 0;
foreach (var term in terms)
{
double v1 = 0;
double v2 = 0;
if (TermFWByGlobal[term].Freq > 1)
{
if (TermFWByType.ContainsKey(0, term) && TermFWByType.ContainsKey(1, term))
{
v1 = GetTermFreq(doc1, doc2, 0, doc1, term) * GetTermWeight(doc1, doc2, 0, doc1, term);
v2 = GetTermFreq(doc1, doc2, 1, doc2, term) * GetTermWeight(doc1, doc2, 1, doc2, term);
}
}
f += v1 * v2;
f1 += v1 * v1;
f2 += v2 * v2;
}
double similarity = -1;
if (f1 * f2 > 0)
{
similarity = f / (Math.Sqrt(f1 * f2));
}
return(similarity);
}
