static void Main(string[] args)
{
string model = @"C:\BigData\NLPmodels\FastText\aviation-caseinsensitive";
if (args.Length > 0)
{
model = args[0];
}
//var words = File.ReadAllLines(model + @".vec").Skip(2).Select((l) => new WordAndSim() { word = l.Split(' ').First() }).ToList();
//words.RemoveAll(x => x.word.Length < 6);
var fastTextModel = new fastText(model + @".bin");
var words = fastTextModel.GetWords();
//var utterances = File.ReadAllLines(@"C:\stanford-nlp\classifier_training\test.tsv").Select(l => new IntentExample() { Intent = l.Split('\t').First(), Example = l.Split('\t').Last().ToLowerInvariant() }).ToList();
while (true)
{
Console.Write("\nWord: "); var w1 = Console.ReadLine();
Console.WriteLine("\nMost similar:");
fastTextModel.GetMostSimilar(w1, 20).ForEach(ws => Console.WriteLine("\t" + ws.Item1.PadLeft(15) + " " + ws.Item2.ToString("0.00")));
Console.WriteLine("\nLeast similar:");
fastTextModel.GetLeastSimilar(w1, 5).ForEach(ws => Console.WriteLine("\t" + ws.Item1.PadLeft(15) + " " + ws.Item2.ToString("0.00")));
//Console.WriteLine();
//Console.Write("Parent: "); var parent = Console.ReadLine();
//double[] averageDiff = new double[fastTextModel.GetVectorSize()];
//double count = 0;
//while(true)
//{
// Console.Write("Child : "); var child = Console.ReadLine();
// if(string.IsNullOrWhiteSpace(child)) { break; }
// var tmpdiff= fastTextModel.GetWordDifference(child, parent);
// averageDiff = fastText.Add(averageDiff, tmpdiff);
//}
//fastText.Multiply(averageDiff, 1 / count);
//Console.Write("New Parent : "); var newParent = Console.ReadLine();
//Console.Write("New Child : "); var newChild = Console.ReadLine();
////var diff = fastTextModel.GetWordDifference(child, parent);
//var newDiff = fastTextModel.GetWordDifference(newChild,newParent);
//Console.WriteLine(string.Join("; ", averageDiff.Select(a => a.ToString("0.00"))));
//Console.WriteLine(string.Join("; ", newDiff.Select(a => a.ToString("0.00"))));
//Console.WriteLine("Similarity between diff vectors:" + fastText.CalculateCosineSimilarity(averageDiff, newDiff));
//if(string.IsNullOrWhiteSpace(parent) || string.IsNullOrWhiteSpace(newParent)) { break; }
//var newChildVector = fastText.Add(fastTextModel.GetWordVector(newParent), averageDiff);
//Console.WriteLine("Similarity between projected new parent and new child: " + fastTextModel.GetWordSimilarity(newChild, newChildVector));
//foreach (var w in words)
//{
// w.sim = fastTextModel.GetWordSimilarity(w.word, newChildVector);
//}
//words.Sort((a, b) => b.sim.CompareTo(a.sim));
//Console.WriteLine("Most similar:");
//foreach (var w in words.Take(20))
//{
// Console.WriteLine($"\t{w.word} -> {w.sim}");
//}
////words.Reverse();
////Console.WriteLine();
////Console.WriteLine("Least similar:");
////foreach (var w in words.Take(5))
////{
//// Console.WriteLine($"\t{w.word} -> {w.sim}");
////}
//Console.WriteLine();
}
fastText.Release();
//while (true)
//{
// Console.Write("First word: "); var w1 = Console.ReadLine();
// Console.Write("Second word: "); var w2 = Console.ReadLine();
// Console.WriteLine($"Similarity between {w1} and {w2} is {fastText.GetWordSimilarity(w1, w2)}");
// Console.WriteLine();
//}
}
