private async Task OnNamedEntityRecognize()
{
try
{
resBosonNamedEntity = await BosonAIHelper.NamedEntityRecognize(textInput.Text.Trim());
if (resBosonNamedEntity.entity.Count > 0)
{
for (int i = 0; i <= resBosonNamedEntity.entity.Count - 1; i++)
{
int nStart = Convert.ToInt32(resBosonNamedEntity.entity[i][0]);
int nEnd = Convert.ToInt32(resBosonNamedEntity.entity[i][1]);
List <string> list = resBosonNamedEntity.word.Skip(nStart).Take(nEnd - nStart).ToList();
string strEntity = "";
foreach (var item in list)
{
strEntity += item;
}
NLPWord nlp = new NLPWord
{
word = strEntity,
width = strEntity.Length * 20,
bgcolor = NameEntityHelper.GetNameEntityColor_Boson(resBosonNamedEntity.entity[i][2])
};
NamedEntityItems.Add(nlp);
}
}
}
catch { }
}
private async void OnBosonAINamedEntityRecognize(object sender, RoutedEventArgs e)
{
animationView.Visibility = Visibility.Visible;
try
{
resBoson = await BosonAIHelper.NamedEntityRecognize(textInput.Text.Trim());
if (resBoson.entity.Count > 0)
{
SampleItems.Clear();
for (int i = 0; i <= resBoson.entity.Count - 1; i++)
{
int nStart = Convert.ToInt32(resBoson.entity[i][0]);
int nEnd = Convert.ToInt32(resBoson.entity[i][1]);
List <string> list = resBoson.word.Skip(nStart).Take(nEnd - nStart).ToList();
string strEntity = "";
foreach (var item in list)
{
strEntity += item;
}
NLPWord nlp = new NLPWord
{
word = strEntity,
width = strEntity.Length * 20,
bgcolor = NameEntityHelper.GetNameEntityColor_Boson(resBoson.entity[i][2])
};
SampleItems.Add(nlp);
}
}
}
catch { }
animationView.Visibility = Visibility.Collapsed;
}
private async Task OnSummary()
{
string res = await BosonAIHelper.SummaryAnalysis(textInput.Text.Trim());
if (res != null)
{
textSummary.Text = res;
}
}
private async Task OnClassify()
{
resBosonClassify = await BosonAIHelper.ClassifyNews(textInput.Text.Trim());
if (resBosonClassify != null)
{
sliderClassify.Value = resBosonClassify.area + 0.5;
}
}
private async Task OnSegTag()
{
resBosonSegTag = await BosonAIHelper.WordSegAndTag(textInput.Text.Trim());
if (resBosonSegTag != null && resBosonSegTag.tag.Count > 0)
{
for (int i = 0; i <= resBosonSegTag.tag.Count - 1; i++)
{
NLPWord nlp = new NLPWord
{
word = resBosonSegTag.word[i],
width = resBosonSegTag.word[i].Length * 20,
bgcolor = PosTagHelper.GetPosColor_Boson(resBosonSegTag.tag[i])
};
SegTagItems.Add(nlp);
}
}
}
private async Task OnEmotionAnalysis()
{
resBosonEmotion = await BosonAIHelper.EmotionAnalysis(textInput.Text.Trim());
if (resBosonEmotion != null)
{
if ((Application.Current as App).strCurrentLanguage.ToLower().Equals("zh-cn"))
{
// Create a new chart data point for each value you want in the PieSeries
var sliceOne = new ChartDataModel {
Value = resBosonEmotion.positive, Title = "正面"
};
var sliceTwo = new ChartDataModel {
Value = resBosonEmotion.negtive, Title = "负面"
};
// Add those items to the list
chartItems.Add(sliceOne);
chartItems.Add(sliceTwo);
}
else
{
// Create a new chart data point for each value you want in the PieSeries
var sliceOne = new ChartDataModel {
Value = resBosonEmotion.positive, Title = "Positive"
};
var sliceTwo = new ChartDataModel {
Value = resBosonEmotion.negtive, Title = "Negtive"
};
// Add those items to the list
chartItems.Add(sliceOne);
chartItems.Add(sliceTwo);
}
MyDoughnutSeries.ItemsSource = chartItems;
}
}
private async Task OnGetSuggest()
{
List <string> list = await BosonAIHelper.GetSuggest(textInput.Text.Trim());
if (list != null && list.Count > 0)
{
var brush = (SolidColorBrush)Application.Current.Resources["SystemControlHighlightListAccentLowBrush"];
for (int i = 0; i <= list.Count - 1; i++)
{
string[] arr = list[i].Split(',');
int relative = Convert.ToInt32(Convert.ToDouble(arr[0]) * 100);
NLPWord nlp = new NLPWord
{
word = arr[1] + " (" + relative + ")",
//width = resBosonSegTag.word[i].Length * 20,
bgcolor = "#99CC67"//brush.Color.ToString()
};
SuggestItems.Add(nlp);
}
}
}
