/// <summary>
/// 情感分析
/// </summary>
/// <param name="input"></param>
/// <returns></returns>
public RES SentimentAnalysis(string input)
{
try
{
Credential cred = new Credential
{
SecretId = secretId,
SecretKey = secretKey
};
ClientProfile clientProfile = new ClientProfile();
HttpProfile httpProfile = new HttpProfile();
httpProfile.Endpoint = ("nlp.ap-shanghai.tencentcloudapi.com");
clientProfile.HttpProfile = httpProfile;
NlpClient client = new NlpClient(cred, "ap-guangzhou", clientProfile);
SentimentAnalysisRequest req = new SentimentAnalysisRequest();
string strParams = JSON.ToJson(new { Text = input });
req = SentimentAnalysisRequest.FromJsonString <SentimentAnalysisRequest>(strParams);
SentimentAnalysisResponse resp = client.SentimentAnalysis(req).
ConfigureAwait(false).GetAwaiter().GetResult();
return(RES.OK(resp));
}
catch (Exception ex)
{
return(RES.FAIL(ex.Message));
}
}
/// <summary>
/// 情感分析接口能够对带有情感色彩的主观性文本进行分析、处理、归纳和推理，识别出用户的情感倾向，是积极还是消极，并且提供各自概率。
///
/// 该功能基于千亿级大规模互联网语料和LSTM、BERT等深度神经网络模型进行训练，并持续迭代更新，以保证效果不断提升。
/// </summary>
/// <param name="req"><see cref="SentimentAnalysisRequest"/></param>
/// <returns><see cref="SentimentAnalysisResponse"/></returns>
public SentimentAnalysisResponse SentimentAnalysisSync(SentimentAnalysisRequest req)
{
JsonResponseModel <SentimentAnalysisResponse> rsp = null;
try
{
var strResp = this.InternalRequestSync(req, "SentimentAnalysis");
rsp = JsonConvert.DeserializeObject <JsonResponseModel <SentimentAnalysisResponse> >(strResp);
}
catch (JsonSerializationException e)
{
throw new TencentCloudSDKException(e.Message);
}
return(rsp.Response);
}
public SentimentAnalysisResponse Post(SentimentAnalysisRequest request)
{
if (request != null && request?.Sentiments.Count > 0)
{
List <SentimentData> sentimentDatas = new List <SentimentData>();
foreach (string s in request.Sentiments)
{
sentimentDatas.Add(new SentimentData()
{
SentimentText = s
});
}
SentimentAnalysis sentimentAnalysis = new SentimentAnalysis();
MLContext mlContext = new MLContext();
TrainTestData splitDataView = sentimentAnalysis.LoadData(mlContext);
ITransformer model = sentimentAnalysis.BuildAndTrainModel(mlContext, splitDataView.TrainSet);
sentimentAnalysis.Evaluate(mlContext, model, splitDataView.TestSet);
//UseModelWithSingleItem(mlContext, model);
return(sentimentAnalysis.PredictSentiments(mlContext, model, sentimentDatas));
}
return(null);
}
public async Task <CloudmersiveNLPResponse> CloudmersiveNLPResponseAsync(string type, string url)
{
string CloudmersiveApiKey = _config["CloudmersiveApiKey"];
string scrapeResult = await ScrapeNewsSiteByUrlAsync(url);
// Configure API key authorization: Apikey
Configuration.Default.AddApiKey("Apikey", CloudmersiveApiKey); // Get an API key at, https://account.cloudmersive.com/
var apiInstance = new AnalyticsApi();
if (type == "sentimentality")
{
var input = new SentimentAnalysisRequest(scrapeResult); // SentimentAnalysisRequest | Input sentiment analysis request
try
{
// Perform Sentiment Analysis and Classification on Text
SentimentAnalysisResponse cloudmersiveResult = apiInstance.AnalyticsSentiment(input);
CloudmersiveNLPResponse cloudmersiveNLPResponse = new CloudmersiveNLPResponse
{
Successful = cloudmersiveResult.Successful,
SentimentClassificationResult = cloudmersiveResult.SentimentClassificationResult,
SentimentScoreResult = cloudmersiveResult.SentimentScoreResult,
SentenceCount = cloudmersiveResult.SentenceCount,
};
return(cloudmersiveNLPResponse);
}
catch (Exception e)
{
return(null);
}
}
else if (type == "subjectivity")
{
var input = new SubjectivityAnalysisRequest(scrapeResult); // SentimentAnalysisRequest | Input sentiment analysis request
try
{
// Perform Subjectivity Analysis and Classification on Text
SubjectivityAnalysisResponse cloudmersiveResult = apiInstance.AnalyticsSubjectivity(input);
CloudmersiveNLPResponse cloudmersiveNLPResponse = new CloudmersiveNLPResponse
{
Successful = cloudmersiveResult.Successful,
SubjectivityScoreResult = cloudmersiveResult.SubjectivityScoreResult,
SentenceCount = cloudmersiveResult.SentenceCount,
};
return(cloudmersiveNLPResponse);
}
catch (Exception e)
{
return(null);
}
}
else
{
return(null);
}
}
public async Task <ActionResult <SentimentAnalysisResponse> > Analyse([FromBody] SentimentAnalysisRequest sentimentAnalysisRequest)
{
var sentiment = await this.textAnalyticsService.AnalyseSentiment(sentimentAnalysisRequest.Content);
return(this.MapResult(sentiment));
}
