public static string[] NGramify(string line, int n = 2)
{
List <string> ngrams = new List <string>();
//clean
char[] trimchars = { ',' };
line = line.ToLower().Trim(trimchars).Trim();
line = EkwOAnalyze.CleanWord(line);
//notStopWord
foreach (string stopword in stopWords)
{
line = line.Replace(stopword, "");
}
//neg
line = line.Replace(" not ", "+not not+");
line = line.Replace(" no ", "+no no+");
char[] space = { ' ' };
string[] splits = line.Split(space, StringSplitOptions.RemoveEmptyEntries);
for (int i = 1; i < splits.Length; i++)
{
string gram = splits[i - 1] + " " + splits[i];
gram = gram.Replace("+not not+", " not ");
gram = gram.Replace("+no no+", " no ");
gram = gram.Replace("+", " ");
ngrams.Add(gram);
}
//for (int i = 0; i < splits.Length; i++)
//{
// string gram = splits[i];
// gram = gram.Replace("+", " ");
// ngrams.Add(gram);
//}
return(ngrams.ToArray());
}
static void Main(string[] args)
{
// DataTable table = new DataTable();
// table.Columns.Add("Sex");
// table.Columns.Add("Height", typeof(double));
// table.Columns.Add("Weight", typeof(double));
// table.Columns.Add("FootSize", typeof(double));
// //training data.
// table.Rows.Add("male", 6, 180, 12);
// table.Rows.Add("male", 5.92, 190, 11);
// table.Rows.Add("male", 5.58, 170, 12);
// table.Rows.Add("male", 5.92, 165, 10);
// table.Rows.Add("female", 5, 100, 6);
// table.Rows.Add("female", 5.5, 150, 8);
// table.Rows.Add("female", 5.42, 130, 7);
// table.Rows.Add("female", 5.75, 150, 9);
// table.Rows.Add("transgender", 4, 200, 5);
// table.Rows.Add("transgender", 4.10, 150, 8);
// table.Rows.Add("transgender", 5.42, 190, 7);
// table.Rows.Add("transgender", 5.50, 150, 9);
//Classifier classifier = new Classifier();
//classifier.TrainClassifier(table);
//classifier.Store("gender.csv");
//classifier.load("gender.csv");
/*
* Classifier classifier = new Classifier();
*
* classifier.TrainClassifier(
* SadHappyObj("sads.vcb-labelled",
* "joys.vcb-labelled",
* "obj.vcb-labelled",
* 10000)
* );
* classifier.Store("sentiobj.csv");
*/
//classifier.load("senti.csv");
//Anlyze("sads.vcb-labelled",
// "joys.vcb-labelled",
// 10000
// );
//Test("test.vcb-labelled", "POS.test.report.csv", 10000);
//Console.WriteLine(classifier.Classify(new double[] { 6, 130, 10}));
//string[] ng = NGramClassifier.NGramify("I do not like fish");
//NGramClassifier.printArrayOfStrings(ng);
//NGramClassifier ngc = new NGramClassifier();
//ngc.recordLine("I do not like fish", -1);
//ngc.recordLine("I hate fish", -1);
//ngc.recordLine("I love fish", +1);
//ngc.recordLine("We are human being", 0);
//NGCTrain("sads.txt", "joys.txt", "obj.txt", 10000);
//return;
//NGCTest("test.txt", "NGC.test.repo.csv", 10000);
//BothTest("test.vcb-labelled", "NGC+POS.test.report.csv", 10000);
/******* EkwOG *****************/
EkwOAnalyze EkwOA = new EkwOAnalyze();
//EkwOA.TEkwP("obj.vcb-labelled", "TEkwP_small", 111);
//EkwOA.TEkwP("sample.undup.vcb-labelled", "TEkwP_sample", -1);
//EkwOA.genEkwBigraph("TEkwP_small.xml");
//EkwOA.genEkwBigraph("TEkwP_sample.xml");
//EkwOA.genEEgraph("sample", 350, 2);
string basicFile = "xob/sample";
EkwOAnalyze.AllNounsEntity = true;
EkwOAnalyze.UsersEntity = true;
//EkwOAnalyze.RemoveDupLines(basicFile + ".vcb-labelled", basicFile + ".undup.vcb-labelled");
//EkwOA.TEkwP(basicFile + ".undup.vcb-labelled", basicFile + "_TEkwP", -1);
EkwOA.genEkwBigraph(basicFile + "_TEkwP.xml", basicFile);
EkwOA.genEEgraph(basicFile, 450, 2, 0.35, false);
EkwOA.BFS(basicFile + ".E.bfs.csv");
EkwOA.BFS_Image(basicFile + ".png", 1);
EkwOA.Communitize(basicFile + "_Communities.xml", 0.0, 1);
Console.WriteLine("final kw count: " + EkwOA.FinalKW(basicFile));
//EkwOA.BFS_Image(basicFile + ".All.png", -1);
//Console.WriteLine( int.MaxValue );
//OpinGram("bankrupt");
//Console.Read();
}
