public async Task Summarize()
{
TextAnalysisClient Client = new TextAnalysisClient(Config.TextAnalysisApiKey);
string fname = @"Data\wap.txt";
StorageFolder InstallationFolder = Windows.ApplicationModel.Package.Current.InstalledLocation;
var file = await InstallationFolder.GetFileAsync(fname);
var stream = await file.OpenReadAsync();
var sr = new StreamReader(stream.AsStreamForRead());
int b = 0; // BOOK
int c = 0; // Chapter
int p = 0; // Paragraph
StringBuilder sb = new StringBuilder();
TextAnalysisDocumentStore Store = new TextAnalysisDocumentStore();
while (!sr.EndOfStream)
{
var s = await sr.ReadLineAsync();
if (s.Contains("BOOK"))
{
b++;
c = 0;
if (b > 2)
{
break;
}
continue;
}
if (s.Contains("CHAPTER"))
{
if (sb.Length > 20)
{
var key = $"b{b}c{c}p{p}";
Store.documents.Add(new TextAnalysisDocument(key, "en", sb.ToString()));
}
sb.Clear();
if (Store.documents.Count > 0)
{
var R = await Client.ExtractKeyphrases(Store);
StringBuilder z = new StringBuilder();
z.AppendLine($"CHAPTER {c}");
foreach (var d in R.documents)
{
z.AppendLine(string.Join(",", d.keyPhrases));
}
Summary.Text += z.ToString();
}
Store.documents.Clear();
c++;
p = 0;
continue;
}
if (s.Trim().Equals(string.Empty))
{
if (sb.Length > 20)
{
var key = $"b{b}c{c}p{p}";
if (Store.documents.Count > 0 && Store.documents.Last().text.Length + sb.ToString().Length < 5000)
{
System.Diagnostics.Debug.WriteLine($"Last {Store.documents.Last().text.Length}, sb {sb.Length}");
Store.documents.Last().text += "\n\r" + sb.ToString();
}
else
{
Store.documents.Add(new TextAnalysisDocument(key, "en", sb.ToString()));
}
}
sb.Clear();
p++;
continue;
}
sb.AppendLine(s);
}
}
public async Task Analyze()
{
TextAnalysisClient Client = new TextAnalysisClient(Config.TextAnalysisApiKey);
TextAnalysisLocalClient LocalClient = new TextAnalysisLocalClient()
{
Sensitivity = 30, Bias = 1
};
string fname = @"Data\wap.txt";
StorageFolder InstallationFolder = Windows.ApplicationModel.Package.Current.InstalledLocation;
var file = await InstallationFolder.GetFileAsync(fname);
var stream = await file.OpenReadAsync();
var sr = new StreamReader(stream.AsStreamForRead());
int b = 0; // BOOK
int c = 0; // Chapter
int p = 0; // Paragraph
double mp = 0; // most positive score
double mn = 1; // most negative score
StringBuilder sb = new StringBuilder();
TextAnalysisDocumentStore Store = new TextAnalysisDocumentStore();
while (!sr.EndOfStream)
{
var s = await sr.ReadLineAsync();
if (s.Contains("BOOK"))
{
b++;
c = 0;
if (b > 2)
{
break;
}
continue;
}
if (s.Contains("CHAPTER"))
{
if (sb.Length > 20)
{
var key = $"b{b}c{c}p{p}";
Store.documents.Add(new TextAnalysisDocument(key, "en", sb.ToString()));
}
sb.Clear();
if (Store.documents.Count > 2)
{
await Task.Delay(3000); // Pause to make sure service is not called to frequently
// Analyze sentiment locally using Local Client (list of keywords)
var RL = LocalClient.AnalyzeSentiment(Store);
var rl = RL.documents.Count == 0 ? 0 :
(from x in RL.documents // compute average score for the subchapter
select x.score).Average();
ItemsLocal.Add(new DataItem($"b{b}c{c}", (int)(rl * 100)));
// Anlyze sentiment properly using cognitive web service
var R = await Client.AnalyzeSentiment(Store);
var r = R.documents.Count == 0 ? 0 :
(from x in R.documents
select x.score).Average();
Items.Add(new DataItem($"b{b}c{c}", (int)(r * 100)));
// Now go through each document passage and find
// passages with best /worst scores and display them
foreach (var x in R.documents)
{
if (x.score >= mp)
{
mp = x.score;
pos.Text = x.text;
posh.Text = $"Positive score={mp}";
}
if (x.score <= mn)
{
mn = x.score;
neg.Text = x.text;
negh.Text = $"Negative score={mn}";
}
}
}
Store.documents.Clear();
c++;
p = 0;
continue;
}
if (s.Trim().Equals(string.Empty))
{
if (sb.Length > 20)
{
var key = $"b{b}c{c}p{p}";
Store.documents.Add(new TextAnalysisDocument(key, "en", sb.ToString()));
}
sb.Clear();
p++;
continue;
}
sb.AppendLine(s);
}
}
public ImapResponder(TextAnalysisClient textAnalysis, ImapOptions options)
{
_textAnalysisClient = textAnalysis;
_options = options;
}
