示例#1
0
 private void ResetAll()
 {
     SegTagItems.Clear();
     NamedEntityItems.Clear();
     chartItems.Clear();
     sliderClassify.Value = sliderTencentClassify.Value = 0;
     textSummary.Text     = "";
     KeywordsItems.Clear();
     SuggestItems.Clear();
 }
示例#2
0
        private async Task GetTencentAIResponse()
        {
            try
            {
                resTencentPosTag = await TencentAIHelper.WordPositionTagging(textInput.Text.Trim());

                if (resTencentPosTag != null && resTencentPosTag.ret == 0 && resTencentPosTag.msg == "ok")
                {
                    SegTagItems.Clear();
                    listBaseTokens = resTencentPosTag.data.base_tokens;
                    listMixTokens  = resTencentPosTag.data.mix_tokens;
                }

                resTencentProperNouns = await TencentAIHelper.WordProperNouns(textInput.Text.Trim());

                if (resTencentProperNouns != null && resTencentProperNouns.ret == 0 && resTencentProperNouns.msg == "ok")
                {
                    NamedEntityItems.Clear();
                    foreach (var item in resTencentProperNouns.data.ner_tokens)
                    {
                        NLPWord nlp = new NLPWord
                        {
                            word    = item.word,
                            width   = item.length * 20,
                            bgcolor = NameEntityHelper.GetNameEntityColor_Tencent(item.types[0].ToString())
                        };
                        NamedEntityItems.Add(nlp);
                    }
                }

                resTencentSynonym = await TencentAIHelper.WordSynonym(textInput.Text.Trim());

                if (resTencentSynonym != null && resTencentSynonym.ret == 0 && resTencentSynonym.msg == "ok")
                {
                    SuggestItems.Clear();
                    foreach (var item in resTencentSynonym.data.syn_tokens)
                    {
                        NLPWord nlp = new NLPWord
                        {
                            word    = item.ori_word.word,
                            width   = item.ori_word.length * 20,
                            bgcolor = "#9acd32"
                        };
                        SuggestItems.Add(nlp);

                        foreach (var iitem in item.syn_words)
                        {
                            string  strWeight = (Convert.ToInt32(iitem.weight * 100)).ToString();
                            NLPWord inlp      = new NLPWord
                            {
                                word = iitem.word + "(" + strWeight + ")",
                                //width = item.ori_word.length * 20,
                                bgcolor = "#99CC67"
                            };
                            SuggestItems.Add(inlp);
                        }
                    }
                }

                resTencentComponent = await TencentAIHelper.WordComponent(textInput.Text.Trim());

                if (resTencentComponent != null && resTencentComponent.ret == 0 && resTencentComponent.msg == "ok")
                {
                    sliderTencentClassify.Value = resTencentComponent.data.intent + 0.5;
                }
                else if (resTencentComponent != null && resTencentComponent.ret == 16393)
                {
                    sliderTencentClassify.Value = 0.5;
                }

                resTencentEmotionPolar = await TencentAIHelper.WordEmotionPolar(textInput.Text.Trim());

                if (resTencentEmotionPolar != null && resTencentEmotionPolar.ret == 0 && resTencentEmotionPolar.msg == "ok")
                {
                    double positive = 0.0, negtive = 0.0;
                    if (resTencentEmotionPolar.data.polar == 1)
                    {
                        positive = 1;
                        negtive  = 0;
                    }
                    else if (resTencentEmotionPolar.data.polar == -1)
                    {
                        positive = 0;
                        negtive  = 1;
                    }
                    else if (resTencentEmotionPolar.data.polar == 0)
                    {
                        positive = 1;
                        negtive  = 1;
                    }

                    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 = positive, Title = "正面"
                        };
                        var sliceTwo = new ChartDataModel {
                            Value = 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 = positive, Title = "Positive"
                        };
                        var sliceTwo = new ChartDataModel {
                            Value = negtive, Title = "Negtive"
                        };

                        // Add those items to the list
                        chartItems.Add(sliceOne);
                        chartItems.Add(sliceTwo);
                    }

                    MyDoughnutSeries.ItemsSource = chartItems;
                }

                TipServices.TipRecognizeSucceed();
            }
            catch
            {
                if (resTencentPosTag.ret < 0)
                {
                    TipServices.TipSystemError();
                }
                else
                {
                    TipServices.TipRecognizeFailed();
                }
            }
        }