/// <summary>
/// Processes the complex.
/// </summary>
/// <param name="chunkTable">The chunk table.</param>
/// <param name="termTable">The term table.</param>
/// <param name="output">The output.</param>
/// <param name="logger">The logger.</param>
/// <param name="subjects">The subjects.</param>
/// <param name="resolver">The resolver.</param>
/// <returns></returns>
protected lemmaSemanticCloud processAlternative(webLemmaTermTable chunkTable, webLemmaTermTable termTable, lemmaSemanticCloud output, ILogBuilder logger, List <pipelineTaskMCSiteSubject> subjects, ITextResourceResolver resolver)
{
if (output == null)
{
output = new lemmaSemanticCloud();
}
lemmaSemanticConstruct c = new lemmaSemanticConstruct(subjects);
List <webLemmaTerm> allChunks = chunkTable.GetList();
// <--------------------------------- DETECTING THE MOST IMPORTANT TERMS
IEnumerable <webLemmaTerm> vipChunks = null;
if (subjects.Count > 1)
{
vipChunks = allChunks.Where(x => x.documentSetFrequency > settings.documentSetFreqLowLimit);
}
else
{
vipChunks = allChunks;
}
instanceCountCollection <String> lemmaCounter = new instanceCountCollection <string>();
List <List <String> > primaryLemmaList = new List <List <String> >();
foreach (webLemmaTerm chunk in vipChunks)
{
var lemmas = chunk.nominalForm.SplitSmart(" ", "", true, true);
lemmas = lemmas.Where(x => x.Length > 2).ToList();
lemmaCounter.AddInstanceRange(lemmas);
}
c.RelevantTerms = lemmaCounter.getSorted();
lemmaCounter.reCalculate();
foreach (String term in c.RelevantTerms)
{
if (lemmaCounter[term] == lemmaCounter.maxFreq)
{
c.PrimaryTerms.Add(term);
}
else if (lemmaCounter[term] > lemmaCounter.minFreq)
{
c.SecondaryTerms.Add(term);
}
else
{
c.ReserveTerms.Add(term);
}
}
c.CollectRelevantTerms(settings.doReserveTermsForClass);
c.LogConstruct(logger);
// <---------------------------------
var docSetFreq = allChunks.Where(x => c.RelevantTerms.Any(y => x.nominalForm.SplitSmart(" ", "", true, true).Contains(y)));
foreach (webLemmaTerm chunk in docSetFreq)
{
var lemmas = chunk.nominalForm.SplitSmart(" ", "", true, true);
lemmas = lemmas.Where(x => x.Length > 2).ToList();
if (lemmas.Count > 1)
{
lemmas.Sort((x, y) => String.CompareOrdinal(x, y));
c.lemmasList.Add(lemmas);
c.weightDict.Add(lemmas, chunk);
c.nodeNames.AddRange(lemmas, true);
}
}
return(BuildCloud(c, chunkTable, termTable, output, logger, resolver));
}
/// <summary>
/// Processes the position enhanced.
/// </summary>
/// <param name="chunkTable">The chunk table.</param>
/// <param name="termTable">The term table.</param>
/// <param name="output">The output.</param>
/// <param name="logger">The logger.</param>
/// <param name="subjects">The subjects.</param>
/// <param name="resolver">The resolver.</param>
/// <returns></returns>
protected lemmaSemanticCloud processPOSEnhanced(webLemmaTermTable chunkTable, webLemmaTermTable termTable, lemmaSemanticCloud output, ILogBuilder logger, List <pipelineTaskMCSiteSubject> subjects, ITextResourceResolver resolver)
{
List <webLemmaTerm> allChunks = chunkTable.GetList();
if (output == null)
{
output = new lemmaSemanticCloud();
}
// <----------------- PRIMARY
lemmaSemanticConstruct c = new lemmaSemanticConstruct(subjects);
lemmaSemanticConstruct cl = new lemmaSemanticConstruct(subjects);
while (c != cl)
{
c = cl;
cl = lemmaSemanticConstruct.NextIteration(cl, resolver, allChunks, settings, subjects, logger);
if (cl.createdInIteration > settings.primaryTermOptimizationIterationLimit)
{
c = cl;
break;
}
if (cl.OptimizationDone)
{
break;
}
}
c = cl;
// <------------------- PRIM
c.CollectRelevantTerms(settings.doReserveTermsForClass);
if (!c.isCaseCloud)
{
c.LogConstruct(logger);
}
// <---------------------------------
var docSetFreq = allChunks.Where(x => c.RelevantTerms.Any(y => x.nominalForm.SplitSmart(" ", "", true, true).Contains(y)));
foreach (webLemmaTerm chunk in docSetFreq)
{
var lemmas = chunk.nominalForm.SplitSmart(" ", "", true, true);
List <String> l_out = new List <string>();
foreach (String lm in lemmas)
{
if (c.NotProcessed(lm))
{
var lu = resolver.GetLexicUnit(lm, logger);
if (lu == null)
{
c.TrashBin.AddUnique(lm);
}
else
{
var tg = lu.GetTagFromGramTags <pos_type>(pos_type.none);
if (tg.ContainsAny(new pos_type[] { pos_type.N, pos_type.A }))
{
c.ReserveTerms.AddUnique(lm);
l_out.Add(lm);
}
else
{
c.TrashBin.AddUnique(lm);
}
}
}
else
{
if (!c.TrashBin.Contains(lm))
{
l_out.Add(lm);
}
}
}
if (l_out.Count > 1)
{
l_out.Sort((x, y) => String.CompareOrdinal(x, y));
c.lemmasList.Add(l_out);
c.weightDict.Add(l_out, chunk);
c.nodeNames.AddRange(l_out, true);
}
}
return(BuildCloud(c, chunkTable, termTable, output, logger, resolver));
}