protected override void CalculateRatingLogic()
{
TextVectorCell[] cells = Review.Vector.GetCells().ToArray();
(double Probability, double Normalization, VectorData Vector)result = Model.GetVector(cells);
VectorData vector = result.Vector;
if (vector == null ||
vector.Length == 0)
{
Rating = Review.CalculateRawRating();
return;
}
var bias = vector.RHO;
var fallbackWeight = 0.1;
VectorCell lexicon = default;
foreach (VectorCell item in vector.Cells)
{
var cell = (TextVectorCell)item.Data;
if (cell.Name == Constants.RATING_STARS)
{
lexicon = item;
}
if (cell.Item != null)
{
var word = (IWordItem)cell.Item;
Add(new SentimentValue(word, word.Text, new SentimentValueData(item.Calculated, SentimentSource.AdjustedSVM)));
}
else
{
bias += item.Calculated;
}
}
var notAddedSentiments = new List <SentimentValue>();
foreach (SentimentValue sentimentValue in Review.GetAllSentiments())
{
if (!ContainsSentiment(sentimentValue.Owner))
{
notAddedSentiments.Add(sentimentValue);
}
}
if (lexicon != null)
{
var totalWords = Review.GetAllSentiments().Length;
fallbackWeight = Math.Abs(lexicon.Theta) / totalWords;
}
if (notAddedSentiments.Count > 0)
{
foreach (SentimentValue sentiment in notAddedSentiments)
{
Add(new SentimentValue(sentiment.Owner, sentiment.Span, new SentimentValueData(sentiment.DataValue.Value * fallbackWeight, SentimentSource.AdjustedCalculated)));
}
}
if (TotalSentiments > 0)
{
Add(new SentimentValue(
WordOccurrence.CreateBasic(Constants.BIAS, POSTags.Instance.JJ),
"BIAS",
new SentimentValueData(bias, SentimentSource.AdjustedSVM)));
}
if (Rating.HasValue)
{
if (Rating.IsPositive.Value &&
result.Probability < 0.5)
{
log.LogDebug("Mistmatch in sentiment with machine prediction: {0} - {1}", Rating.IsPositive, result.Probability);
}
}
}
