private static string NormalizeQuery(string strQuery)
{
StringBuilder sb = new StringBuilder();
//Break query string by given dictionary
wordseg.Segment(strQuery, tokens, false);
for (int i = 0; i < tokens.tokenList.Count; i++)
{
//Normalize term and if the term is empty, ignore it
WordSeg.Token wbTkn = tokens.tokenList[i];
string strTerm = NormalizeTerm(wbTkn.strTerm).Trim();
if (strTerm.Length == 0)
{
continue;
}
sb.Append(strTerm);
sb.Append(" ");
}
return(sb.ToString().Trim());
}
private static bool StatTermWeightInQuery(List <QueryItem> qiList)
{
//Check each query item in qiList, and save good items for term weight calucating
int goodQueryItemCount = 0;
foreach (QueryItem item in qiList)
{
List <Token> tknList = new List <Token>();
bool bIgnored = false;
//Break query string by given dictionary
wordseg.Segment(item.strQuery, tokens, false);
for (int i = 0; i < tokens.tokenList.Count; i++)
{
//Normalize term and if the term is empty, ignore it
WordSeg.Token wbTkn = tokens.tokenList[i];
string strTerm = wbTkn.strTerm.Trim();
if (strTerm.Length == 0)
{
continue;
}
//check duplicate terms in a query
//If duplicated terms is found, drop current query
for (int j = 0; j < tknList.Count; j++)
{
if (tknList[j].strTerm == strTerm)
{
//found the duplicated term
bIgnored = true;
break;
}
}
if (bIgnored == true)
{
//Ignore the query with duplicated term
break;
}
//Save the token into the list
Token token = new Token();
token.strTerm = strTerm;
tknList.Add(token);
}
if (bIgnored == false)
{
item.tokenList = tknList;
goodQueryItemCount++;
}
else
{
item.tokenList = null;
}
}
//The flag for checking whether query is sub-query or super-query for all other queries in the cluster
bool bEntireCluster = false;
for (int i = 0; i < qiList.Count; i++)
{
QueryItem selQueryItem = qiList[i];
if (selQueryItem.tokenList == null)
{
continue;
}
Dictionary <Token, int> termHash2Freq = new Dictionary <Token, int>();
int totalFreq = selQueryItem.freq;
int queryInCluster = 1;
foreach (Token item in selQueryItem.tokenList)
{
termHash2Freq.Add(item, selQueryItem.freq);
}
//Check selQueryItem's sub-query and super-query, and statistic frequency
for (int j = 0; j < qiList.Count; j++)
{
if (i != j && qiList[j].tokenList != null)
{
List <Token> joinBList = new List <Token>();
//Try to find selQueryItem's sub-query
if (AsubOfB(qiList[j].tokenList, selQueryItem.tokenList, joinBList) == true)
{
//Found a sub-query of selQueryItem
//Increase the cluster, query and term's frequency
queryInCluster++;
totalFreq += qiList[j].freq;
foreach (Token item in joinBList)
{
termHash2Freq[item] += qiList[j].freq;
}
}
//Try to find selQueryItem's super-query
else if (AsuperOfB(qiList[j].tokenList, selQueryItem.tokenList, joinBList) == true)
{
//Found a super-query of selQueryItem
//Increase the cluster, query and term's frequency
queryInCluster++;
totalFreq += qiList[j].freq;
foreach (Token item in joinBList)
{
termHash2Freq[item] += qiList[j].freq;
}
}
}
}
if (queryInCluster < MIN_CLUSTER_SIZE)
{
//The generated cluster is too small, ignore current query item
selQueryItem.tokenList = null;
continue;
}
if (queryInCluster == goodQueryItemCount && selQueryItem.strQuery.Length >= 2)
{
//All other queries are current query's sub or super set.
bEntireCluster = true;
}
foreach (Token item in selQueryItem.tokenList)
{
double fWeight = ((double)termHash2Freq[item]) / ((double)totalFreq);
item.fWeight = fWeight;
}
}
return(bEntireCluster);
}
