public ProbabilityDictionary(ProbabilityDictionary <T> original)
{
dict = original.dict;
Count = original.Count;
totalCount = original.totalCount;
rand = new Random();
}
public string GetTagForWord(string word, TagDictionary markovChains)
{
ProbabilityDictionary <string> possibleTags = null;
try
{
possibleTags = dict[word];
} catch { }
if (possibleTags != null)
{
if (possibleTags.Count == 1)
{
//Only one tag is possbile. Return that one.
return(possibleTags.GetRandomItem());
}
else
{
//Multiple tags could be possible.
//Use markov chains and tag probability to nominate a tag.
}
}
else
{
//Any tag could be possible. Rely on markov chains only.
}
return("{{ goddamit steve }}");
}
public String TagForWord(string word, String previousTag = null)
{
ProbabilityDictionary <string> possibleTags = null;
try
{
possibleTags = tagsForWords.GetProbabilityDictionaryFor(word);
} catch {}
try
{
if (possibleTags != null)
{
if (possibleTags.Count == 1)
{
//Only one tag is possible for this word. Return that.
return(possibleTags.GetRandomItem());
}
else
{
//Multiple possible tags. Choose with help of markov chains.
try
{
return(markovChains.GetProbabilityDictionaryFor(previousTag).GetItemWithHighestProbablity());
}
catch
{
return(possibleTags.GetItemWithHighestProbablity());
}
}
}
else
{
//No possible tags known. Rely on markov chains only.
//Console.WriteLine(markovChains.GetProbabilityDictionaryFor(previousTag));
return(markovChains.GetProbabilityDictionaryFor(previousTag).GetItemWithHighestProbablity());
}
}
catch (Exception e)
{
//Console.WriteLine(e.StackTrace);
return(null);
}
}