private void button2_Click(object sender, EventArgs e)
{
string text = ReadPdfFile(textBox1.Text);
string[] sentences = SplitSentences(text);
Dictionary <string, int> dictionary = new Dictionary <string, int>();
summary summ = new summary();
List <string> tokenSentence = new List <string>();
List <string> nonStopWords = new List <string>();
List <string> posTag = new List <string>();
List <string> names = new List <string>();
string[] models = new string[] { "date", "location", "money", "organization", "percentage", "person", "time" };
List <TFIDFFrequency> tFrequency = new List <TFIDFFrequency>();
foreach (string sentence in sentences)
{
tokenSentence = mTokenizer.Tokenize(sentence).ToList();
names.Add(mNameFinder.GetNames(models, sentence));
}
foreach (string word in StopwordTool._stops.Keys)
{
while (tokenSentence.Contains(word))
{
tokenSentence.Remove(word);
}
}
posTag = mPosTagger.Tag(tokenSentence.ToArray()).ToList();
double[][] inputs = TFIDF.Transform(sentences, 0);
inputs = TFIDF.Normalize(inputs);
// Display the output.
for (int index = 0; index < inputs.Length; index++)
{
foreach (double value in inputs[index])
{
tFrequency.Add(new TFIDFFrequency {
Sentence = sentences[index], TFValue = value
});
}
}
foreach (string word in tokenSentence)
{
if (word.Length >= 3)
{
if (dictionary.ContainsKey(word))
{
dictionary[word]++;
}
else
{
dictionary[word] = 1;
}
}
}
foreach (string name in names)
{
if (name.Length >= 3)
{
if (dictionary.ContainsKey(name))
{
dictionary[name]++;
}
else
{
dictionary[name] = 1;
}
}
}
var sortedDict = (from entry in dictionary orderby entry.Value descending select entry).ToDictionary(pair => pair.Key, pair => pair.Value);
int count2 = 1;
int result2 = 1;
int.TryParse(textBox3.Text, out result2);
foreach (KeyValuePair <string, int> pair in sortedDict)
{
summ.Sentences.Add(pair.Key);
count2++;
if (count2.Equals(result2))
{
break;
}
}
int count1 = 1;
int result1 = 1;
int.TryParse(textBox3.Text, out result1);
var sortedtFIDF = from data in tFrequency orderby data.TFValue descending select data;
foreach (var vr in sortedtFIDF)
{
summ.Sentences.Add(vr.Sentence);
count1++;
if (count1.Equals(result1))
{
break;
}
}
string summary = string.Join("\r\n", summ.Sentences.ToArray());
richTextBox1.Text = summary;
}
private void button3_Click(object sender, EventArgs e)
{
string text;
string word = textBox2.Text;
WebClient web = new WebClient();
HtmlAgilityPack.HtmlDocument Htmldoc = new HtmlAgilityPack.HtmlDocument();
Process.Start("https://en.wikipedia.org/wiki/" + word);
byte[] byteArray = web.DownloadData(new Uri("https://en.wikipedia.org/wiki/" + word));
Stream stream = new MemoryStream(byteArray);
Htmldoc.Load(stream);
FileStream fs = new FileStream("D:\\htmltext2.pdf", FileMode.Create, FileAccess.Write);
Document pdfDoc = new Document();
PdfWriter writer = PdfWriter.GetInstance(pdfDoc, fs);
pdfDoc.Open();
foreach (HtmlNode node in Htmldoc.DocumentNode.SelectNodes("//p"))
{
text = node.InnerText.Trim();
pdfDoc.Add(new Paragraph(text));
}
pdfDoc.Close();
string htmltext = ReadPdfFile("D:\\htmltext2.pdf");
string[] sentences = SplitSentences(htmltext);
Dictionary <string, int> dictionary = new Dictionary <string, int>();
summary summ = new summary();
List <string> tokenSentence = new List <string>();
List <string> nonStopWords = new List <string>();
List <string> posTag = new List <string>();
List <string> names = new List <string>();
string[] models = new string[] { "date", "location", "money", "organization", "percentage", "person", "time" };
List <TFIDFFrequency> tFrequency = new List <TFIDFFrequency>();
foreach (string sentence in sentences)
{
tokenSentence = mTokenizer.Tokenize(sentence).ToList();
names.Add(mNameFinder.GetNames(models, sentence));
}
foreach (string stopWord in StopwordTool._stops.Keys)
{
while (tokenSentence.Contains(stopWord))
{
tokenSentence.Remove(stopWord);
}
}
posTag = mPosTagger.Tag(tokenSentence.ToArray()).ToList();
double[][] inputs = TFIDF.Transform(sentences, 0);
inputs = TFIDF.Normalize(inputs);
// Display the output.
for (int index = 0; index < inputs.Length; index++)
{
foreach (double value in inputs[index])
{
tFrequency.Add(new TFIDFFrequency {
Sentence = sentences[index], TFValue = value
});
}
}
foreach (string tokenWord in tokenSentence)
{
if (tokenWord.Length >= 3)
{
if (dictionary.ContainsKey(tokenWord))
{
dictionary[tokenWord]++;
}
else
{
dictionary[tokenWord] = 1;
}
}
}
foreach (string name in names)
{
if (name.Length >= 3)
{
if (dictionary.ContainsKey(name))
{
dictionary[name]++;
}
else
{
dictionary[name] = 1;
}
}
}
var sortedDict = (from entry in dictionary orderby entry.Value descending select entry).ToDictionary(pair => pair.Key, pair => pair.Value);
int count2 = 1;
int result2 = 1;
int.TryParse(textBox4.Text, out result2);
foreach (KeyValuePair <string, int> pair in sortedDict)
{
summ.Sentences.Add(pair.Key);
count2++;
if (count2.Equals(result2))
{
break;
}
}
int count1 = 1;
int result1 = 1;
int.TryParse(textBox4.Text, out result1);
var sortedtFIDF = from data in tFrequency orderby data.TFValue descending select data;
foreach (var vr in sortedtFIDF)
{
summ.Sentences.Add(vr.Sentence);
count1++;
if (count1.Equals(result1))
{
break;
}
}
string summary = string.Join("\r\n", summ.Sentences.ToArray());
richTextBox1.Text = summary;
}
