public Sentence(AnalysisContext context, string sentence)
{
this.context = context;
Text = sentence;
Entities = new List<int>();
SentimentWords = new List<int>();
}
public BaesianClassifier(AnalysisContext context)
{
this.context = context;
foreach(var w in context.SentimentWords)
{
positiveDict.Add(w, new int[2]);
negativeDict.Add(w, new int[2]);
}
}
public static AnalysisContext CreateContext()
{
AnalysisContext cont = new AnalysisContext();
var lines = File.ReadAllLines(Constants.WordsFile);
foreach(var line in lines)
{
var pp = line.Split(new[] {';'}, StringSplitOptions.RemoveEmptyEntries);
if(pp.Length>1)
{
var w = new Word() {Base = pp[1], id = int.Parse(pp[0])};
for (int i = 2; i < pp.Length; i++)
w.Variations.AddLast(pp[i]);
cont.allwords[w.id] = w;
}
}
lines = File.ReadAllLines(Constants.EntitiesFile);
foreach(var l in lines)
{
var pp = l.Split(';');
if (pp.Length == 1)
cont.Entities.Add(cont.allwords[int.Parse(pp[0])]);
else
{
var f = new Frase();
foreach(var p in pp)
{
f.Add(cont.allwords[int.Parse(p)]);
}
cont.Entities.Add(f);
}
}
lines = File.ReadAllLines(Constants.FrasesFile);
foreach (var l in lines)
{
var pp = l.Split(';');
if (pp.Length == 1)
cont.SentimentWords.Add(cont.allwords[int.Parse(pp[0])]);
else
{
var f = new Frase();
foreach (var p in pp)
{
f.Add(cont.allwords[int.Parse(p)]);
}
cont.SentimentWords.Add(f);
}
}
return cont;
}
