public static KnowledgeClassifier <string> Advice(this KnowledgeClassifier <string> classifier, string nodeData, string cls)
{
var node = GraphLayerBase.CreateReference(nodeData);
classifier.Advice(node, cls);
return(classifier);
}
private Graphs E(string node1, string edgeName, string node2)
{
_layer.AddEdge(
GraphLayerBase.CreateReference(node1),
edgeName,
GraphLayerBase.CreateReference(node2)
);
return(this);
}
public Loader(string path)
{
_reader = new StreamReader(path, Encoding.UTF8);
DataLayer = new ExplicitLayer();
Console.WriteLine("Counting lines: " + path);
var lineCount = 0;
var edges = new HashSet <string>();
var myInterning = new Dictionary <string, string>();
while (!_reader.EndOfStream)
{
var line = _reader.ReadLine();
++lineCount;
}
_reader.BaseStream.Seek(0, SeekOrigin.Begin);
Console.WriteLine("Loading graph(" + lineCount + "): " + path);
var lastPercent = 0;
var lineIndex = 0;
while (!_reader.EndOfStream)
{
var line = _reader.ReadLine();
var parts = split(line);
var source = intern(parts[0]);
var edge = intern(parts[1]);
var target = intern(parts[2]);
var sourceNode = GraphLayerBase.CreateReference(source);
var targetNode = GraphLayerBase.CreateReference(target);
_nodes.Add(sourceNode);
_nodes.Add(targetNode);
DataLayer.AddEdge(sourceNode, edge, targetNode);
UtteranceParser.RegisterEntity(target);
++lineIndex;
var currentPercent = 100 * lineIndex / lineCount;
if (currentPercent != lastPercent)
{
GC.Collect();
Console.WriteLine(currentPercent);
lastPercent = currentPercent;
}
}
}
private NodeReference N(string name)
{
UtteranceParser.RegisterEntity(name);
return(GraphLayerBase.CreateReference(name));
}
private NodeReference N(string name)
{
return(GraphLayerBase.CreateReference(name.Replace(" ", "_")));
}
