static void Stem(Sample sample)
{
EnglishPorter2Stemmer stemmer = new EnglishPorter2Stemmer();
Dictionary <string, int> stemmedWords = new Dictionary <string, int>();
foreach (var word in sample.words)
{
var value = word.Value;
var key = word.Key;
var stemmedKey = stemmer.Stem(key).Value;
if (stemmedWords.ContainsKey(stemmedKey))
{
var valueHolder = stemmedWords.GetValueOrDefault(stemmedKey);
stemmedWords.Remove(stemmedKey);
stemmedWords.Add(stemmedKey, value + valueHolder);
}
else
{
stemmedWords.Add(stemmedKey, value);
}
}
sample.words.Clear();
sample.words = stemmedWords;
}
public void Stem_WithBatchData_StemsAllWordsCorrectly(string unstemmed, string expected)
{
var stemmer = new EnglishPorter2Stemmer();
var stemmed = stemmer.Stem(unstemmed).Value;
Assert.AreEqual(expected, stemmed);
}
public List <string> parseText(string text)
{
var charText = text.ToCharArray();
string token = string.Empty;
List <string> textTokens = new List <string>();
var ep2s = new EnglishPorter2Stemmer();
for (int i = 0; i < charText.Length; i++)
{
char c = charText[i];
if (char.IsLetterOrDigit(c) || IsArabic(c)) //Accept english and arabic only
{
token += c;
}
else
{
if (!string.IsNullOrEmpty(token))
{
if (token.All(ch => char.IsLetterOrDigit(ch)))
{
textTokens.Add(ep2s.Stem(token).Value); //stem then add
}
else //for arabic
{
textTokens.Add(token);
}
token = string.Empty;
}
}
}
if (!string.IsNullOrEmpty(token)) //for last token
{
if (token.All(ch => char.IsLetterOrDigit(ch)))
{
textTokens.Add(ep2s.Stem(token).Value); //stem then add
}
else //for arabic
{
textTokens.Add(token);
}
token = string.Empty;
}
return(textTokens);
}
public List <string> goStemmer(string[] filteredTokens)
{
outList = new List <string>();
foreach (string token in filteredTokens)
{
outWord = toStem.Stem(token);
outList.Add(outWord.Value);
}
return(outList);
}
private string CutPatternWords(string[] words, string patternWordsType)
{
string output = "";
string patternSign = String.Concat(">", patternWordsType.Substring(0, 1).ToLower());
_cutWords.Add(patternSign, new LinkedList <string>());
foreach (string word in words)
{
if (_wordsTypes[patternWordsType].Contains(patternSign == ">v" ? stemmer.Stem(word).Value : word)) // if verb stemming it
{
output += patternSign + " ";
_cutWords[patternSign].AddLast(patternSign == ">v" ? stemmer.Stem(word).Value : word);
}
else
{
output += word + " ";
}
}
return(output.Trim());
}
public IActionResult Search(SearchViewModel viewModel)
{
var searchTokens = viewModel.search.Split(" ");
List <string> stemmedTokens = new List <string>();
foreach (string s in searchTokens)
{
stemmedTokens.Add(ps.Stem(s).Value);
}
List <List <float> > links = new List <List <float> >();
foreach (string s in stemmedTokens)
{
JArray j = new JArray();
List <float> index = new List <float>();
try
{
index = invIndex.jsonData[s].ToObject <List <float> >();
}
catch
{
continue;
}
links.Add(index);
}
List <float> commonList = new List <float>();
int ctr = 0;
foreach (List <float> l in links)
{
if (ctr == 0)
{
commonList.AddRange(l);
ctr++;
continue;
}
commonList = commonList.Intersect <float>(l).ToList();
}
foreach (var i in links)
{
foreach (float f in i)
{
if (!commonList.Contains(f))
{
commonList.Add(f);
}
}
}
ViewData["List"] = commonList;
return(View());
}
public void Stem_WithBatchData_StemsAllWordsCorrectly()
{
// Arrange
var stemmer = new EnglishPorter2Stemmer();
var row = TestContext.DataRow;
var unstemmed = row[0].ToString();
var expected = row[1].ToString();
// Act
var stemmed = stemmer.Stem(unstemmed).Value;
// Asssert
Assert.AreEqual(expected, stemmed);
}
public string stemming(string webcontent)
{
//the code for stemming was already implemented online. I just added the project in my solution.
EnglishPorter2Stemmer stem = new EnglishPorter2Stemmer();
string[] words = webcontent.Split(' ');
string stemmedwords = "";
foreach (var word in words)
{
stemmedwords = stemmedwords + " " + stem.Stem(word).Value;
}
return(stemmedwords);
}
public void Stem_WithBatchData_StemsAllWordsCorrectly()
{
var tests = StemBatchTestCaseSource.GetTestCaseData();
foreach (var batchTestDataModel in tests)
{
// Arrange
var stemmer = new EnglishPorter2Stemmer();
var unstemmed = batchTestDataModel.Unstemmed;
var expected = batchTestDataModel.Expected;
// Act
var stemmed = stemmer.Stem(unstemmed).Value;
// Asssert
Assert.AreEqual(expected, stemmed);
}
}
public void Handle()
{
for (int k = 0; k < _documents[_documentIndex].Count; k++)
{
TFIDFNote tfidfNote = new TFIDFNote();
tfidfNote.Word = _documents[_documentIndex][k];
// Fill the values list for each document:
// With word stemming:
EnglishPorter2Stemmer englishPorter = new EnglishPorter2Stemmer();
tfidfNote.ValuesList = new List <TFIDFValue>();
for (int j = 0; j < _documents.Count; j++)
{
tfidfNote.ValuesList.Add(
new TFIDFValue
{
DocumentName = _filePathList[j],
Value = GetTFIDFValue(englishPorter.Stem(_documents[_documentIndex][k]), _documents[j], _documents)
});
}
DocumentDictionary.Add(tfidfNote);
}
}
public Task <string[]> Apply(string[] input)
{
EnglishPorter2Stemmer stemmer = new EnglishPorter2Stemmer();
return(Task.FromResult(input?.Select(s => stemmer.Stem(s)).Where(w => !string.IsNullOrWhiteSpace(w)).ToArray()));
}
public override string Stem(string word)
{
return(stemmer.Stem(word).Value);
}
public static string Stem(string word)
{
return(_stemmer.Stem(word).Value);
}
public void optimizeQueryTokens(ref List <string> tokens, bool INSERT_AND = false)
{
var ep2s = new EnglishPorter2Stemmer();
if (_Algorithm != Algorithm.TFIDFSearchModel)
{
for (int i = 0; i < tokens.Count; i++)
{
if (tokens[i] != "(" && tokens[i] != ")" && tokens[i] != "NOT" && tokens[i] != "AND" && tokens[i] != "OR")
{
//Insert Missinng ORs
if (i + 1 < tokens.Count)
{
if (tokens[i + 1] != "(" && tokens[i + 1] != ")" && tokens[i + 1] != "AND" && tokens[i + 1] != "OR")
{
if (INSERT_AND)
{
tokens.Insert(i + 1, "AND");
}
else
{
tokens.Insert(i + 1, "OR");
}
}
}
//Stem Tokens using porter2Stemmer
if (tokens[i].All(ch => char.IsLetterOrDigit(ch))) //if english
{
tokens[i] = ep2s.Stem(tokens[i].ToLower()).Value; //stem then add
}
}
else if (tokens[i] == ")")
{
if (i + 1 < tokens.Count)
{
if (tokens[i + 1] != ")" && tokens[i + 1] != "AND" && tokens[i + 1] != "OR")
{
if (INSERT_AND)
{
tokens.Insert(i + 1, "AND");
}
else
{
tokens.Insert(i + 1, "OR");
}
}
}
}
}
}
else // if(_Algorithm == Algorithm.TFIDFSearchModel)
{
for (int i = 0; i < tokens.Count; i++)
{
//Stem Tokens using porter2Stemmer
if (tokens[i].All(ch => char.IsLetterOrDigit(ch))) //if english
{
tokens[i] = ep2s.Stem(tokens[i].ToLower()).Value; //stem then add
}
}
}
}
public void Stem_WithBatchData_StemsAllWordsCorrectly()
{
// Arrange
var stemmer = new EnglishPorter2Stemmer();
var row = TestContext.DataRow;
var unstemmed = row[0].ToString();
var expected = row[1].ToString();
// Act
var stemmed = stemmer.Stem(unstemmed).Value;
// Asssert
Assert.AreEqual(expected, stemmed);
}
protected void Button1_Click(object sender, EventArgs e)
{
String query = Query.Text;
Mean.Text = "";
Results.Items.Clear();
NonResults.Items.Clear();
Suggested.Items.Clear();
Proximity.Items.Clear();
if (query.Length == 0)
{
return;
}
queryTerms = new List <String>();
StemmedQueryTerms = new List <String>();
TE = new IRTest_Entities();
bool Spelling = Spell.Checked;
bool Soundex = Sound.Checked;
bool ExactSearch = true;
if (query[0] != '"')
{
ExactSearch = false;
}
//Retrieving Query Terms
int Begin = 0;
int End = query.Length;
String Term = "";
if (ExactSearch == true)
{
Begin++;
End--;
}
for (int i = Begin; i < End; i++)
{
if (query[i] == ' ')
{
if (Term.Length > 0)
{
String TTerm = "";
for (int j = 0; j < Term.Length; j++)
{
TTerm += Char.ToLower(Term[j]);
}
queryTerms.Add(TTerm);
EnglishPorter2Stemmer stemmer = new EnglishPorter2Stemmer();
String STTERM = stemmer.Stem(TTerm).Value;
StemmedQueryTerms.Add(STTERM);
}
Term = "";
}
else
{
Term += query[i];
if (i == End - 1)
{
String TTerm = "";
for (int j = 0; j < Term.Length; j++)
{
TTerm += Char.ToLower(Term[j]);
}
queryTerms.Add(TTerm);
EnglishPorter2Stemmer stemmer = new EnglishPorter2Stemmer();
String STTERM = stemmer.Stem(TTerm).Value;
StemmedQueryTerms.Add(STTERM);
}
}
}
//Spelling Correction
if (Spelling == true)
{
String CorrectedWords = "";
for (int i = 0; i < queryTerms.Count; i++)
{
List <String> SimilarWords = new List <String>();
String Tquery = "$";
Tquery += queryTerms[i];
Tquery += "$";
for (int j = 0; j < Tquery.Length - 1; j++)
{
String Gram = Tquery.Substring(j, 2);
List <String> CandidateTerms = new List <String>();
foreach (Bigram BG in TE.Bigrams)
{
if (Gram.Equals(BG.gram))
{
String DictionaryTerms = BG.terms;
String Temp = "";
for (int u = 0; u < DictionaryTerms.Length; u++)
{
if (DictionaryTerms[u] == ' ')
{
if (Temp.Length > 0)
{
String TTemp = "$";
TTemp += Temp;
TTemp += "$";
CandidateTerms.Add(TTemp);
}
Temp = "";
}
else
{
Temp += DictionaryTerms[u];
if (u == DictionaryTerms.Length - 1)
{
String TTemp = "$";
TTemp += Temp;
TTemp += "$";
CandidateTerms.Add(TTemp);
}
}
}
break;
}
}
for (int u = 0; u < CandidateTerms.Count; u++)
{
String Candidate = CandidateTerms[u];
double CommonGrams = 0;
double QueryGrams = Tquery.Length - 1;
double TermGrams = Candidate.Length - 1;
for (int f = 0; f < Tquery.Length - 1; f++)
{
for (int ff = 0; ff < Candidate.Length - 1; ff++)
{
if (Tquery.Substring(f, 2).Equals(Candidate.Substring(ff, 2)))
{
CommonGrams++;
break;
}
}
}
double Jaccard = (2.0 * CommonGrams) / (QueryGrams + TermGrams);
Jaccard *= 100.0;
if (Jaccard >= 45)
{
if (!(SimilarWords.Contains(Candidate)))
{
SimilarWords.Add(Candidate);
}
}
}
}
List <int> Distances = new List <int>();
for (int f = 0; f < SimilarWords.Count; f++)
{
String Temp = "";
for (int ff = 1; ff < SimilarWords[f].Length - 1; ff++)
{
Temp += SimilarWords[f][ff];
}
int _EditDistance = EditDistance(queryTerms[i], Temp);
Distances.Add(_EditDistance);
}
//Sorting
for (int write = 0; write < SimilarWords.Count; write++)
{
for (int sort = 0; sort < SimilarWords.Count - 1; sort++)
{
if (Distances[sort] > Distances[sort + 1])
{
int temp = Distances[sort + 1];
Distances[sort + 1] = Distances[sort];
Distances[sort] = temp;
String TSTR = SimilarWords[sort + 1];
SimilarWords[sort + 1] = SimilarWords[sort];
SimilarWords[sort] = TSTR;
}
}
}
if (SimilarWords.Count > 0)
{
CorrectedWords += SimilarWords[0].Substring(1, SimilarWords[0].Length - 2);
}
else
{
CorrectedWords += "NULL";
}
if (i < queryTerms.Count - 1)
{
CorrectedWords += ' ';
}
for (int f = 0; f < SimilarWords.Count; f++)
{
Suggested.Items.Add(SimilarWords[f].Substring(1, SimilarWords[f].Length - 2));
}
}
Mean.Text = CorrectedWords;
}
//Soundex
if (Soundex == true)
{
List <int> DOCS = new List <int>();
List <int> FREQS = new List <int>();
String Code = ComputeSoundex(queryTerms[0]);
foreach (SoundCode SC in TE.SoundCodes)
{
if (Code.Equals(SC.code))
{
String PTerms = SC.terms;
String Temp2 = "";
for (int i = 0; i < PTerms.Length; i++)
{
if (PTerms[i] == ' ')
{
if (Temp2.Length > 0)
{
EnglishPorter2Stemmer stemmer = new EnglishPorter2Stemmer();
String STEMMED = stemmer.Stem(Temp2).Value;
foreach (II_Stemming II in TE.II_Stemming)
{
if (STEMMED == II.name)
{
int _docid = (int)II.docid;
int _frequency = (int)II.frequency;
DOCS.Add(_docid);
FREQS.Add(_frequency);
}
}
}
Temp2 = "";
}
else
{
Temp2 += PTerms[i];
if (i == PTerms.Length - 1)
{
EnglishPorter2Stemmer stemmer = new EnglishPorter2Stemmer();
String STEMMED = stemmer.Stem(Temp2).Value;
foreach (II_Stemming II in TE.II_Stemming)
{
if (STEMMED == II.name)
{
int _docid = (int)II.docid;
int _frequency = (int)II.frequency;
DOCS.Add(_docid);
FREQS.Add(_frequency);
}
}
}
}
}
break;
}
}
//Sorting
for (int write = 0; write < FREQS.Count; write++)
{
for (int sort = 0; sort < FREQS.Count - 1; sort++)
{
if (FREQS[sort] < FREQS[sort + 1])
{
int temp = FREQS[sort + 1];
FREQS[sort + 1] = FREQS[sort];
FREQS[sort] = temp;
int TINT = DOCS[sort + 1];
DOCS[sort + 1] = DOCS[sort];
DOCS[sort] = TINT;
}
}
}
List <String> URLS = new List <String>();
foreach (EnglishPage EP in TE.EnglishPages.ToList())
{
URLS.Add(EP.URL);
}
for (int i = 0; i < DOCS.Count; i++)
{
Results.Items.Add(URLS[DOCS[i] - 1]);
Proximity.Items.Add(FREQS[i].ToString());
}
//for (int i = 0; i < SimilarWords.Count; i++) Results.Items.Add(SimilarWords[i]);
}
else if (queryTerms.Count > 0)
{
TERMS = new Dictionary <String, Dictionary <int, List <int> > >();
DBNames = new List <String>();
List <String> URLS = new List <String>();
foreach (EnglishPage EP in TE.EnglishPages.ToList())
{
URLS.Add(EP.URL);
}
foreach (II_Stemming II in TE.II_Stemming.ToList())
{
DBNames.Add(II.name);
if (StemmedQueryTerms.Contains(II.name) == true)
{
if (TERMS.ContainsKey(II.name) == true)
{
if (TERMS[II.name].ContainsKey((int)II.docid) == false)
{
String POS = II.positions;
int C = 0;
List <int> POSS = new List <int>();
for (int i = 1; i < POS.Length; i++)
{
if (POS[i] == ' ')
{
POSS.Add(C);
C = 0;
}
else
{
C = (C * 10) + ((int)(POS[i] - '0'));
if (i == POS.Length - 1)
{
POSS.Add(C);
}
}
}
TERMS[II.name].Add((int)II.docid, POSS);
}
}
else
{
TERMS.Add(II.name, new Dictionary <int, List <int> >());
String POS = II.positions;
int C = 0;
List <int> POSS = new List <int>();
for (int i = 1; i < POS.Length; i++)
{
if (POS[i] == ' ')
{
POSS.Add(C);
C = 0;
}
else
{
C = (C * 10) + ((int)(POS[i] - '0'));
if (i == POS.Length - 1)
{
POSS.Add(C);
}
}
}
TERMS[II.name].Add((int)II.docid, POSS);
}
}
}
if (ExactSearch == true)
{
DOCS_EXACT = new Dictionary <int, int>();
int[] DOCS_COUNT = new int[1610];
List <int> NON_CANDIDATE_DOCS = new List <int>();
foreach (KeyValuePair <String, Dictionary <int, List <int> > > EE in TERMS)
{
foreach (KeyValuePair <int, List <int> > EE2 in EE.Value)
{
DOCS_COUNT[EE2.Key]++;
}
}
for (int i = 1; i <= 1600; i++)
{
if (DOCS_COUNT[i] < StemmedQueryTerms.Count && DOCS_COUNT[i] > 0)
{
NON_CANDIDATE_DOCS.Add(i);
}
}
bool TR = SOLVE(0, queryTerms.Count, 0, 0);
List <int> DOCS_ = new List <int>();
List <int> Freqs_ = new List <int>();
foreach (KeyValuePair <int, int> EE in DOCS_EXACT)
{
DOCS_.Add(EE.Key);
Freqs_.Add(EE.Value);
}
//sorting
for (int write = 0; write < Freqs_.Count; write++)
{
for (int sort = 0; sort < Freqs_.Count - 1; sort++)
{
if (Freqs_[sort] < Freqs_[sort + 1])
{
int temp = Freqs_[sort + 1];
Freqs_[sort + 1] = Freqs_[sort];
Freqs_[sort] = temp;
int TINT = DOCS_[sort + 1];
DOCS_[sort + 1] = DOCS_[sort];
DOCS_[sort] = TINT;
}
}
}
for (int i = 0; i < DOCS_.Count; i++)
{
Results.Items.Add(URLS[DOCS_[i] - 1]);
Proximity.Items.Add(Freqs_[i].ToString());
}
//NON COMMON RESULTS
for (int i = 0; i < NON_CANDIDATE_DOCS.Count; i++)
{
NonResults.Items.Add(URLS[NON_CANDIDATE_DOCS[i] - 1]);
}
}
else
{
DOCS_RANDOM = new List <int>();
DOCS_DIS = new List <int>();
NON_CANDIDATE = new List <int>();
SOLVE_RANDOM(queryTerms.Count);
for (int i = 0; i < DOCS_RANDOM.Count; i++)
{
Results.Items.Add(URLS[DOCS_RANDOM[i] - 1]);
Proximity.Items.Add(DOCS_DIS[i].ToString());
}
//NON COMMON RESULTS
for (int i = 0; i < NON_CANDIDATE.Count; i++)
{
NonResults.Items.Add(URLS[NON_CANDIDATE[i] - 1]);
}
}
}
}
static void Main(string[] args)
{
List <string> properPlaces = new List <string> {
"usa", "west-germany", "france", "uk", "japan", "canada"
};
List <string> myPlaces = new List <string> {
};
List <string> myBody = new List <string> {
};
List <TestObj> Testowe = new List <TestObj> {
};
DirectoryInfo d = new DirectoryInfo(@"E:\Pulpit\1111111"); //Assuming Test is your Folder
FileInfo[] Files = d.GetFiles("*.sgm"); //Getting Text files
int o = 0;
foreach (FileInfo file in Files)
{
const Int32 BufferSize = 128;
//string path = @"E:\Pulpit\1111111\reut2-001.sgm";
using (var fileStream = File.OpenRead(file.FullName))
using (var streamReader = new StreamReader(fileStream, Encoding.UTF8, true, BufferSize))
{
//int i = 0;
String line;
String wynik = "";;
line = streamReader.ReadLine();
while ((line = streamReader.ReadLine()) != null)
{
//Podmieniam znaki specjalne na takie ktore nie wchodza w konflikt z xml
wynik += ReplaceHexadecimalSymbols(line);
//if (line.Contains("<PLACES>"))
//{ }
//Console.WriteLine(line);
//i++;
//if (i > 20)
//{ break; }
}
var Myreplacedxml = "<root>" + wynik + "</root>";
//wynik += ("<root>" + wynik + "</root>");
XmlSerializer Serializer = new XmlSerializer(typeof(root));
root result;
using (TextReader reader = new StringReader(Myreplacedxml))
result = (root)Serializer.Deserialize(reader);
foreach (rootREUTERS rootREUTER in result.REUTERS)
{
if (rootREUTER.PLACES.Length != 1)
{
continue;
}
else if (!properPlaces.Contains(rootREUTER.PLACES[0]))
{
continue;
}
else
{
if (!(rootREUTER.TEXT.BODY is null))
{
myPlaces.Add(rootREUTER.PLACES[0]);
myBody.Add(rootREUTER.TEXT.BODY);
//Console.WriteLine(rootREUTER.TEXT.BODY);
}
//Console.WriteLine(rootREUTER.PLACES[0]);
}
}
//Console.ReadKey();
// Process line
}
//odczyt jenego pliku
//o++;
//if(o > 9) {
// break;
Console.WriteLine("Processing " + file.FullName + "...");
// }
}
EnglishPorter2Stemmer stemmer = new EnglishPorter2Stemmer();
List <int> feature2 = new List <int> {
};
//int i = 0;
//while (myBody[i] != null)
//Tutaj testuje stemowanie i wybieranie + wpisywanie cech do listyw obiekcie
List <string> allwords = new List <string> {
};
Dictionary <string, int> wordsDictionary = new Dictionary <string, int>();
for (int i = 0; i < myBody.Count; i++)
{
char[] separator = { '.', ',', ' ', '\t', '"', '=', '-', '<', '>', ')', '(', ';' };
string[] worlds = myBody[i].Split(separator);
List <double> feature1 = new List <double> {
};
string pom;
double world7 = 0;
double worldS = 0;
//int world5 = 0;
foreach (string world in worlds)
{
pom = stemmer.Stem(world).Value;
if (!wordsDictionary.ContainsKey(pom))
{
wordsDictionary.Add(pom, 1);
}
else
{
wordsDictionary[pom]++;
}
//Console.WriteLine(pom);
//Zliczam ilosc slow dluzszych powyzej 7 znakow
}
}
foreach (KeyValuePair <string, int> kvp in wordsDictionary)
{
if (kvp.Value > 10)
{
allwords.Add(kvp.Key);
}
}
//double w1 = worldS;
//double w2 = world7;
//double normal = Math.Sqrt((w1*w1) + (w2*w2));
//world7 = world7 / normal;
//worldS = worldS / normal;
// feature1.Add(worldS);
// feature1.Add(world7);
// Testowe.Add(new TestObj(myPlaces[i], feature1));
//Dodaje cechy i tworze obiekty
for (int i = 0; i < myBody.Count; i++)
{
string[] worlds = myBody[i].Split(' ');
List <double> feature1 = new List <double> {
};
string pom;
for (int j = 0; j < worlds.Length; j++)
{
pom = stemmer.Stem(worlds[j]).Value;
worlds[j] = pom;
}
foreach (string world in allwords)
{
//allwords przechowuje wystąpienia słowa, myBody.Count to liczba dokumentów
double counter = 0;
if (worlds.Contains(world))
{
foreach (string wrd in worlds)
{
if (wrd.Equals(world))
{
counter++;
}
}
//tf idf basically, myBody.Count to liczba obiektow aworldsDictionary przechowuje wystapienia slow w calym zbiorze
double pomocy = (double)myBody.Count / (double)wordsDictionary[world];
counter = counter * Math.Log(pomocy);
feature1.Add(counter);
}
else
{
feature1.Add(0);
}
}
Testowe.Add(new TestObj(myPlaces[i], feature1));
}
// Nie jest kolorowo
// zapisuje do pliku formatu csv żeby potem przetworzyć w pythonie
/*
* using (System.IO.StreamWriter file =
* new System.IO.StreamWriter(@"E:\Pulpit\Reuters_reduce_usa.csv"))
* {
* string LineToWrite = "labels,";
* foreach (string line in allwords)
* {
*
* LineToWrite += (line + ",");
*
*
*
* }
*
* file.WriteLine(LineToWrite);
* int liczusa = 0;
* foreach (TestObj testObj in Testowe)
* {
* if ((testObj.label.Equals("usa"))) { liczusa++; }
* if ((liczusa == 10) || (!testObj.label.Equals("usa")))
* {
* LineToWrite = (testObj.label + ",");
* foreach(int feature in testObj.features)
* {
* LineToWrite += feature.ToString() + ",";
* }
* file.WriteLine(LineToWrite);
* if(liczusa == 10) { liczusa = 0; }
*
* }
* }
*
* }
* Console.WriteLine("Zapisywanie ukończone");
*/
// Moje piękne wywołanie algorytmu
KNN(10, Testowe, 5);
double KNN(int k, List <TestObj> objs, int odsetek)
{
double accuracy = 0;
List <string> Predictions = new List <string> {
};
List <TestObj> Tests = new List <TestObj> {
};
List <TestObj> Verification = new List <TestObj> {
};
//dzielę zbior na testowy i testowany
//TODO zrobic mozliwosc wyboru odsetka ele w zb testowym
int DeleteUsa = 0;
int cykle = 0;
int poprawne = 0;
int licz = 1;
foreach (TestObj obj in objs)
{
//Dwa ify do usuwania 9/10 usa
if (obj.label.Equals("usa"))
{
DeleteUsa++;
}
if ((DeleteUsa == 10) || (!obj.label.Equals("usa")))
{
if (licz <= odsetek)
{
Verification.Add(obj);
licz++;
}
else if ((licz > odsetek) && (licz < 10))
{
Tests.Add(obj);
licz++;
}
else
{
Tests.Add(obj);
licz = 1;
}
DeleteUsa = 0;
}
}
Console.WriteLine(Tests.Count + " | " + Verification.Count);
//Tu sie bedzie dzialo
foreach (TestObj oTe in Tests)
{
List <double> Neighbours = new List <double> {
};
List <string> Nlabels = new List <string> {
};
double sqdistance;
int iterator = 0;
foreach (TestObj oVe in Verification)
{
double distance = 0;
int i = 0;
while (i < oVe.features.Count)
{
distance += ((oTe.features[i] - oVe.features[i]) * (oTe.features[i] - oVe.features[i]));
i++;
}
sqdistance = Math.Sqrt(distance);
// Znajduje k nn
if (iterator < k)
{
Neighbours.Add(sqdistance);
Nlabels.Add(oVe.label);
iterator++;
}
else
{
int potato = 0;
while (iterator > potato)
{
if (Neighbours[potato] > sqdistance)
{
Neighbours[potato] = sqdistance;
Nlabels[potato] = oVe.label;
}
potato++;
}
}
}
/*
* //Pora podjac decyzje
* List<string> Ulabels = new List<string> { };
* int j = 0;
* foreach (string label in Nlabels)
* {
* //musi byc petla dla labels nad tym ifem
* int i = 0;
* if (Ulabels.Count == 0)
* {
* Ulabels.Add(label);
* j++;
* }
*
* while (j < Ulabels.Count)
* {
* if (!Ulabels[j].Equals(label))
* {
* Ulabels[j] = label;
*
* }
* j++;
* }
*
* }
*/
List <string> Ulabels = new List <string> {
};
foreach (string place in properPlaces)
{
if (Nlabels.Contains(place))
{
Ulabels.Add(place);
}
}
List <string> truewinner = new List <string> {
};
int x = 0;
int max = 0;
while (x < Ulabels.Count)
{
int counter = 0;
int y = 0;
while (y < Nlabels.Count)
{
if (Ulabels[x].Equals(Nlabels[y]))
{
counter++;
}
y++;
}
if (x == 0)
{
max = counter;
truewinner.Add(Ulabels[x]);
}
else if (counter > max)
{
truewinner.Clear();
truewinner.Add(Ulabels[x]);
}
else if ((counter == max))
{
truewinner.Add(Ulabels[x]);
}
x++;
}
// Console.WriteLine("Kraj przewidziany : " + truewinner[0] + " Kraj faktyczny : " + oTe.label + "\n");
// foreach (string label in Nlabels)
//{
// Console.WriteLine(label + " | ");
//}
if (oTe.label.Equals(truewinner[0]))
{
poprawne++;
//if(!(oTe.label == "usa"))
//{
//Console.WriteLine("Kraj dobrze przewidziany : " + oTe.label);
//}
}
Predictions.Add(truewinner[0]);
cykle++;
// Console.WriteLine("Ilosc cykli: " + cykle);
}
accuracy = (double)poprawne / cykle;
Console.WriteLine("Wynik : " + accuracy);
return(accuracy);
}
Console.ReadKey();
string ReplaceHexadecimalSymbols(string txt)
{
string r = "[\x00-\x08\x0B\x0C\x0E-\x1F\x26]";
return(Regex.Replace(txt, r, "", RegexOptions.Compiled));
}
}
public Tweet CleanTweet(string tweet, bool stemmingFlag, Filter filter, int minWordLength)
{
List <string> tweetWords = new List <string>();
string userName = "";
DateTime tweetDate;
string[] words;
// initialized with default, just in case tweet does not qualify for parsing. It is a bad approach though, but works for the time being
Tweet currentTweet = null;
////// Extract tweet fregments
// tweets without URLs are considered. Assumption: tweets with URLs are probably advertisments
if (!ContainsURL(tweet))
{
string dateString = tweet.Substring(0, 29);
tweetDate = _Util.ConvertToDate(dateString);
// left with user name and tweet contents
tweet = tweet.Substring(30, tweet.Length - 30);
// spliting different parts of tweet => first item is user name and second item is tweet
words = tweet.Split(new char[] { '\t' }, StringSplitOptions.RemoveEmptyEntries);
userName = words[0];
// split here on all dirty characters including space
//words = words[1].Split(dirtyCharacters, StringSplitOptions.RemoveEmptyEntries);
words = Regex.Replace(words[1], acceptableCharactersRegex, " ").Split(new char[] { ' ' }, StringSplitOptions.RemoveEmptyEntries);
bool dropFlag;
foreach (string str in words)
{
int tempNumericCheck;
string keyword = str.Trim().ToLower();
// it will also remove numbers
if (!IsStopWord(keyword) && !tweetWords.Contains <string>(keyword) && !int.TryParse(keyword, out tempNumericCheck))
{
dropFlag = false;
// only word droping filter will work here
// rest of the filter types will work only when all of the data is extracted
if (filter == Filter.WORDS)
{
if (_BagOfWords._RemoveWords.ContainsKey(keyword))
{
_BagOfWords._RemoveWords[keyword] = Convert.ToSingle(_BagOfWords._RemoveWords[keyword]) + 1f;
dropFlag = true;
}
}
if (keyword.Length < minWordLength)
{
// if length of word does not qualitfy, then simply add it in to list of stop words, and set frequency if already existed
if (_BagOfWords._FilteredOutWords.ContainsKey(keyword))
{
_BagOfWords._FilteredOutWords[keyword] = Convert.ToSingle(_BagOfWords._FilteredOutWords[keyword]) + 1f;
}
else
{
_BagOfWords._FilteredOutWords.Add(keyword, 1f);
}
dropFlag = true;
}
// if tweet word is not in filter word
if (!dropFlag)
{
if (stemmingFlag)
{
keyword = stemmer.Stem(keyword).Value;
}
_BagOfWords.Add(keyword);
tweetWords.Add(keyword);
}
} // end of stopword, duplicate and numeric condition check
} // end of foreach word in tweet
//tweet must contain atleast on word
if (tweetWords.Count > 0)
{
_wordsUserList.AddWordsInfo(tweetWords, userName);
_usersWordList.AddUserInfo(userName, tweetWords);
currentTweet = new Tweet(tweetDate, userName, tweetWords);
}
} // end of URL check condition
return(currentTweet);
}
/// <summary>
/// Get list of posting
/// </summary>
/// <param name="index"> inverted index</param>
/// <param name="processor">nomal token processor</param>
/// <returns></returns>
public IList <Posting> GetPostings(IIndex index, ITokenProcessor processor)
{
processor = ((NormalTokenProcessor)processor);
//Normal proccessing of token and split them into literal by *
string[] literals = this.token.Split("*").ToArray();
for (int i = 0; i < literals.Length; i++)
{
List <string> processedToken = processor.ProcessToken(literals[i]);
if (processedToken.Count > 0)
{
if (i == 0)
{
literals[i] = "$" + processedToken[0];
}
else if (i == literals.Length - 1)
{
literals[i] = processedToken[0] + "$";
}
else
{
literals[i] = processedToken[0];
}
}
}
literals = literals.Where(x => !string.IsNullOrEmpty(x) && x != "$").ToArray();
//Gather candidates for each literals
List <List <string> > candidatesList = new List <List <string> >();
foreach (string literal in literals)
{
List <string> candidates = new List <String>();
bool didMerge = false;
//KGram and AND merge results for a literal
List <string> kGramTerms = this.KGramSplitter(literal);
foreach (string kGramTerm in kGramTerms)
{
if (!didMerge)
{
candidates = candidates.Union(this.kGram.getVocabularies(kGramTerm)).ToList();
didMerge = true;
}
else
{
candidates = candidates.Intersect(this.kGram.getVocabularies(kGramTerm)).ToList();
}
}
//Post filtering step
if (candidates.Count > 0)
{
//$literal*
if (literal.ElementAt(0) == '$' && literal.ElementAt(literal.Length - 1) != '$')
{
candidates = candidates.Where(s => s.StartsWith(literal.Substring(1))).ToList();
}
// *literal$
else if (literal.ElementAt(0) != '$' && literal.ElementAt(literal.Length - 1) == '$')
{
candidates = candidates.Where(s => s.EndsWith(literal.Substring(0, literal.Length - 1))).ToList();
}
// *literal*
else if (literal.ElementAt(0) != '$' && literal.ElementAt(literal.Length - 1) != '$')
{
candidates = candidates.Where(s => s.Contains(literal) && !s.StartsWith(literal) && !s.EndsWith(literal)).ToList();
}
candidatesList.Add(candidates);
}
else
{
candidatesList.Add(new List <string>());
}
}
//Generate the final candidates by merging candidates from all literals
List <string> finalCandidates = new List <string>();
for (int i = 0; i < candidatesList.Count; i++)
{
if (i == 0)
{
finalCandidates = finalCandidates.Union(candidatesList[i]).ToList();
}
else
{
finalCandidates = finalCandidates.Intersect(candidatesList[i]).ToList();
}
}
//Stem final candidates and remove duplicate
HashSet <string> stemmedFinalCandidates = new HashSet <string>();
foreach (string s in finalCandidates)
{
stemmedFinalCandidates.Add(stemmer.Stem(s).Value);
}
return(index.GetPostings(stemmedFinalCandidates.ToList()));
}