private static List<TermAndFreq> QueueToList(Util.PriorityQueue<TermAndFreq> queue)
{
var terms = new List<TermAndFreq>();
while (queue.Count > 0)
{
terms.Add(queue.Pop());
}
return terms;
}
/// <summary>
/// Convenience routine to make it easy to return the most interesting words in a document.
/// More advanced users will call <see cref="RetrieveTerms(TextReader, string)"/> directly.
/// </summary>
/// <param name="r"> the source document </param>
/// <param name="fieldName"> field passed to analyzer to use when analyzing the content </param>
/// <returns> the most interesting words in the document </returns>
/// <seealso cref="RetrieveTerms(TextReader, string)"/>
/// <seealso cref="MaxQueryTerms"/>
public string[] RetrieveInterestingTerms(TextReader r, string fieldName)
{
var al = new List <string>(MaxQueryTerms);
Util.PriorityQueue <object[]> pq = RetrieveTerms(r, fieldName);
object cur;
int lim = MaxQueryTerms; // have to be careful, retrieveTerms returns all words but that's probably not useful to our caller...
// we just want to return the top words
while (((cur = pq.Pop()) != null) && lim-- > 0)
{
var ar = (object[])cur;
al.Add(ar[0].ToString()); // the 1st entry is the interesting word
}
return(al.ToArray());
}
/// <summary>
/// Create the More like query from a <see cref="T:Util.PriorityQueue{object[]}"/>
/// </summary>
private Query CreateQuery(Util.PriorityQueue <object[]> q)
{
BooleanQuery query = new BooleanQuery();
object cur;
int qterms = 0;
float bestScore = 0;
while ((cur = q.Pop()) != null)
{
var ar = (object[])cur;
var tq = new TermQuery(new Term((string)ar[1], (string)ar[0]));
if (ApplyBoost)
{
if (qterms == 0)
{
bestScore = ((float)ar[2]);
}
float myScore = ((float)ar[2]);
tq.Boost = boostFactor * myScore / bestScore;
}
try
{
query.Add(tq, Occur.SHOULD);
}
catch (BooleanQuery.TooManyClausesException)
{
break;
}
qterms++;
if (MaxQueryTerms > 0 && qterms >= MaxQueryTerms)
{
break;
}
}
return(query);
}
