private WordObject AddWordObj(string word, string POS)
{
WordObject w = new WordObject(word);
if (POSLib.IsNoun(POS) == true)
{
w.PartOfSpeech = POSLib.NOUN;
}
return w;
}
/// <summary>
/// Add a word to the internal hash table
/// </summary>
/// <param name="word">
/// A <see cref="System.String"/>
/// </param>
/// <returns>
/// A <see cref="System.Boolean"/>
/// </returns>
public bool AddWord(string word, string article)
{
WordObject wordObj;
//article = FindWords.CleanArticle(article);
int position = article.IndexOf(word);
// Add the word to the hash
if (this.words.ContainsKey(word).Equals(false))
{
wordObj = new WordObject(word);
this.words.Add(word, wordObj);
}
// If the word is found in this article, calculate the statistics
wordObj = this.words[word];
// Prior based on total classifiers
if (this.usingPrior == true)
{
if (position >= 0)
{
wordObj.Seen();
}
// Using Dirichlet Prior
double numerator = (double)wordObj.TimesInTraining + 1d;
double denominator = (double)this.timesInTraining + (double)this.totalClassifiers;
double prob = numerator / denominator;
wordObj.SetProb(prob);
}
else if (this.usingLaplace == true)
{
if (position >= 0)
{
wordObj.Seen();
}
// Using Laplace Smoothing
// Add a virtual document for each word
double numerator = (double)wordObj.TimesInTraining + 1d;
double denominator = (double)this.timesInTraining + (double)this.totalWords;
double prob = numerator / denominator;
wordObj.SetProb(prob);
}
else if (this.useMesitmate == true)
{
if (position >= 0)
{
wordObj.Seen();
}
double numerator = (double)wordObj.TimesInTraining + (1d * this.pValue);
double denominator = (double)this.timesInTraining + (double)this.totalWords;
double prob = numerator / denominator;
wordObj.SetProb(prob);
}
// we are not using any "special" techniques
// if the word in this article is found, adjust probabilites
else if (position >= 0)
{
wordObj.Seen();
double prob = ((double)wordObj.TimesInTraining / (double)this.timesInTraining);
wordObj.SetProb(prob);
}
// We have not seen this word before in this classifier
// Change the default to Min Value
else if (wordObj.GetProb() == 0)
{
// We can't let the prob go to zero
// Calculate the M-estimate
double prob = ClassifierObject.GetMinValue();
wordObj.SetProb(prob);
}
return true;
}
