public Marker(NLPProcessor processor, string modelPath)
{
_processor = processor;
_modelPath = modelPath;
Annotation sportSpecificWords = _processor.Annotate(File.ReadAllText(modelPath + "specificwords.txt"));
_sportSpecificWords = NLPCoreHelper.GetLemmas(sportSpecificWords);
File.Delete(modelPath + "specificwords.txt");
StringBuilder builder = new StringBuilder();
foreach (string word in _sportSpecificWords)
{
builder.AppendLine(word);
}
File.WriteAllText(modelPath + "specificwords.txt", builder.ToString());
PersonOccurenceDatabase = new WordOccurenceDatabase();
OrganizationOccurenceDatabase = new WordOccurenceDatabase();
LocationsOccurenceDatabase = new WordOccurenceDatabase();
SportSpecificWordsOccurenceDatabase = new WordOccurenceDatabase();
_categoriesCount = Enum.GetValues(typeof(SportCategory)).Length;
int hiddenLayerCount = (10 * _categoriesCount) / 3;
_classifier = new ActivationNetwork(new SigmoidFunction(), 4 * _categoriesCount, hiddenLayerCount, _categoriesCount);
_teacher = new BackPropagationLearning(_classifier);
Array values = Enum.GetValues(typeof(SportCategory));
_categoryIndex = new Dictionary <SportCategory, int>();
_indexCategory = new Dictionary <int, SportCategory>();
for (int index = 0; index < values.Length; index++)
{
SportCategory category = (SportCategory)values.GetValue(index);
_categoryIndex.Add(category, index);
_indexCategory.Add(index, category);
}
}
