public void GetOccurences()
{
var vector = new SentimentVector();
dictionary.Object.ExtractToVector(vector, new[] { new TestWordItem {
Text = "kill"
} });
dictionary.Object.ExtractToVector(vector, new[] { new TestWordItem {
Text = "kill"
} });
dictionary.Object.ExtractToVector(vector, new[] { new TestWordItem {
Text = "love"
} });
var data = vector.GetOccurences().ToArray();
Assert.AreEqual(8, data.Length);
Assert.AreEqual("Anger", data[0].Data);
Assert.AreEqual(0, data[0].Probability);
Assert.AreEqual("Fear", data[3].Data);
Assert.AreEqual(2, data[3].Probability);
Assert.AreEqual("Sadness", data[5].Data);
Assert.AreEqual(2, data[5].Probability);
Assert.AreEqual("Joy", data[4].Data);
Assert.AreEqual(1, data[4].Probability);
}
private void PopulateAttributes(SentimentVector vector, WordEx word, IWordItem original)
{
var record = nrcDictionary.FindRecord(word);
vector.ExtractData(record);
word.Emotions = record?.GetDefinedCategories().ToArray();
word.Attributes = original.Inquirer.Records.SelectMany(item => item.Description.Attributes).ToArray();
}
protected override void Additional()
{
SentimentVector vector = dictionary.Extract(review.ImportantWords);
foreach (var probability in vector.GetProbabilities().Where(item => item.Probability > 0))
{
AddItem(null, $"DIMENSION_{probability.Data}", probability.Probability);
}
base.Additional();
}
public TrainingClient(ILogger <TrainingClient> log, IClientContext clientContext)
{
this.clientContext = clientContext ?? throw new ArgumentNullException(nameof(clientContext));
if (string.IsNullOrEmpty(clientContext.Context.SvmPath))
{
throw new ArgumentException("Value cannot be null or empty.", nameof(clientContext.Context.SvmPath));
}
this.log = log ?? throw new ArgumentNullException(nameof(log));
SentimentVector = new SentimentVector();
analyze = new AnalyseReviews();
featureExtractor = new MainAspectHandler(new AspectContextFactory());
sentimentVector = new SentimentVector();
}
public void Construct()
{
SentimentVector vector = new SentimentVector();
Assert.AreEqual(0, vector.Anger);
Assert.AreEqual(0, vector.Anticipation);
Assert.AreEqual(0, vector.Disgust);
Assert.AreEqual(0, vector.Fear);
Assert.AreEqual(0, vector.Joy);
Assert.AreEqual(0, vector.Trust);
Assert.AreEqual(0, vector.Sadness);
Assert.AreEqual(0, vector.Surprise);
Assert.AreEqual(0, vector.Total);
Assert.AreEqual(0, vector.TotalSum);
}
public static SentimentVector Extract(this INRCDictionary dictionary, IEnumerable <IWordItem> words)
{
if (dictionary is null)
{
throw new ArgumentNullException(nameof(dictionary));
}
if (words is null)
{
throw new ArgumentNullException(nameof(words));
}
var vector = new SentimentVector();
dictionary.ExtractToVector(vector, words);
return(vector);
}
public TestingClient(ILogger <TestingClient> log, IClientContext clientContext)
{
if (log == null)
{
throw new ArgumentNullException(nameof(log));
}
if (string.IsNullOrEmpty(clientContext.Context.SvmPath))
{
DisableSvm = true;
}
this.clientContext = clientContext ?? throw new ArgumentNullException(nameof(clientContext));
this.log = log;
AspectSentiment = new AspectSentimentTracker(new ContextSentimentFactory());
SentimentVector = new SentimentVector();
}
public void GetProbabilities()
{
var vector = new SentimentVector();
dictionary.Object.ExtractToVector(vector, new[] { new TestWordItem("kill") });
dictionary.Object.ExtractToVector(vector, new[] { new TestWordItem("kill") });
dictionary.Object.ExtractToVector(vector, new[] { new TestWordItem("love") });
var data = vector.GetProbabilities().ToArray();
Assert.AreEqual(8, data.Length);
Assert.AreEqual("Anger", data[0].Data);
Assert.AreEqual(0, data[0].Probability);
Assert.AreEqual("Fear", data[3].Data);
Assert.AreEqual(0.67, Math.Round(data[3].Probability, 2));
Assert.AreEqual("Sadness", data[5].Data);
Assert.AreEqual(0.67, Math.Round(data[5].Probability, 2));
Assert.AreEqual("Joy", data[4].Data);
Assert.AreEqual(0.33, Math.Round(data[4].Probability, 2));
}
public void Save(ProcessingContext context)
{
var vector = new SentimentVector();
if (ExtractStyle)
{
foreach (var word in context.Processed.Words)
{
vector.ExtractData(dictionary.FindRecord(word));
}
}
lock (csvDataOut)
{
csvDataOut.WriteField(context.Original.Id);
csvDataOut.WriteField(context.Original.DocumentTime);
csvDataOut.WriteField(context.Original.Stars);
csvDataOut.WriteField(context.Adjustment.Rating.StarsRating);
csvDataOut.WriteField(context.Review.GetAllSentiments().Length);
if (ExtractStyle)
{
csvDataOut.WriteField(vector.Anger);
csvDataOut.WriteField(vector.Anticipation);
csvDataOut.WriteField(vector.Disgust);
csvDataOut.WriteField(vector.Fear);
csvDataOut.WriteField(vector.Joy);
csvDataOut.WriteField(vector.Sadness);
csvDataOut.WriteField(vector.Surprise);
csvDataOut.WriteField(vector.Trust);
csvDataOut.WriteField(vector.Total);
}
csvDataOut.NextRecord();
csvDataOut.Flush();
}
if (Debug)
{
resultsWriter.WriteObject(context.Processed);
}
}
public static SentimentVector Extract(this INRCDictionary dictionary, IEnumerable <WordEx> words)
{
if (dictionary is null)
{
throw new ArgumentNullException(nameof(dictionary));
}
if (words is null)
{
throw new ArgumentNullException(nameof(words));
}
var vector = new SentimentVector();
foreach (var word in words)
{
vector.ExtractData(dictionary.FindRecord(word));
}
return(vector);
}
public static void ExtractToVector(this INRCDictionary dictionary, SentimentVector vector, IEnumerable <IWordItem> words)
{
if (dictionary is null)
{
throw new ArgumentNullException(nameof(dictionary));
}
if (vector is null)
{
throw new ArgumentNullException(nameof(vector));
}
if (words is null)
{
throw new ArgumentNullException(nameof(words));
}
foreach (var word in words)
{
vector.ExtractData(dictionary.FindRecord(word));
}
}
public Document ReparseDocument(IRatingAdjustment adjustment)
{
if (adjustment?.Review?.Document == null)
{
throw new ArgumentNullException(nameof(adjustment));
}
adjustment.CalculateRating();
var document = new Document();
document.DocumentTime = adjustment.Review.Document.DocumentTime;
document.Stars = adjustment.Review.Document.Stars;
document.Id = adjustment.Review.Document.Id;
document.Author = adjustment.Review.Document.Author;
if (adjustment.Rating != null)
{
document.Stars = adjustment.Rating.StarsRating;
}
bool buildText = false;
if (adjustment.Review.Text != null)
{
document.Text = adjustment.Review.Text;
buildText = true;
}
var vector = new SentimentVector();
foreach (var sentence in adjustment.Review.Sentences)
{
if (string.IsNullOrWhiteSpace(sentence.Text))
{
continue;
}
var sentenceItem = new SentenceItem(sentence.Text);
document.Add(sentenceItem, buildText);
foreach (var wordItem in sentence.Occurrences)
{
var word = WordExFactory.Construct(wordItem);
word.IsStop = wordItem.IsStopWord;
word.Phrase = wordItem.Parent?.Text;
word.NormalizedEntity = wordItem.NormalizedEntity;
word.Span = word.Text;
var sentiment = wordItem.Relationship.Sentiment?.DataValue;
if (sentiment != null)
{
word.Value = sentiment.Value;
word.Span = wordItem.Relationship.Sentiment.Span;
}
word.IsAspect = wordItem.IsFeature;
SentimentValue value = adjustment.GetSentiment(wordItem);
if (value != null)
{
word.CalculatedValue = value.DataValue.Value;
}
else if (word.Value != null)
{
word.CalculatedValue = 0;
}
if (adjustment.Review.Context.ExtractAttributes)
{
PopulateAttributes(vector, word, wordItem);
}
sentenceItem.Add(word);
}
}
document.Text = adjustment.Review.Document.Text;
if (adjustment.Review.Context.ExtractAttributes)
{
document.Attributes = vector.GetProbabilities().ToDictionary(item => item.Data, item => item.Probability.ToString());
}
return(document);
}
public static VectorData GetVector(this SentimentVector vector, NormalizationType normalization)
{
return(vector.GetTree(false).CreateVector(normalization, false));
}