public static DataTable GetDataFromURL(string URL)
{
// Train Dictionary with positive and negative words
Node Positive = Node.CreateMemNodes();
Node Negative = Node.CreateMemNodes();
Dictionary.FillDictionary(Positive, Negative);
// Get Data From Webclient
var url = URL;
clsSerializer objSerializer = new clsSerializer();
var objVenomReviewOverall = objSerializer._download_serialized_json_data <clsJson.Rootobject>(url);
clsJson.Results objRes = new clsJson.Results();
objRes = objVenomReviewOverall.results;
clsJson.Overall[] objOverall; clsJson.Individual[] objIndividual;
objOverall = objRes.Overall; objIndividual = objRes.Individual;
DataTable dtProductData = new DataTable();
dtProductData.Columns.Add("ProductName");
dtProductData.Columns.Add("AverageRating");
dtProductData.Columns.Add("TopComment");
dtProductData.Columns.Add("Interpretation");
dtProductData.Columns.Add("IndividualRating");
dtProductData.Columns.Add("OutofRating");
for (int i = 0; i < objIndividual.Length; i++)
{
string ProductName = objOverall[0].ProductName;
string AvgRating = objOverall[0].AvgRating;
string TopComment = objIndividual[i].TopComment;
string IndividualRating = objIndividual[i].IndividualRating[0];
string TopCommentModified = Dictionary.ModifyInputString(TopComment);
string OutofRating = objIndividual[i].IndividualRating[1];
Algorithm analyzer = new Algorithm(); string Interpretation = "";
Algorithm.EnumCategory result = analyzer.Categorize(Initializer.GetStringsFrom(TopCommentModified), Positive, Negative);
switch (result)
{
case Algorithm.EnumCategory.First:
Interpretation = "Positive";
break;
case Algorithm.EnumCategory.Undetermined:
Interpretation = "Undetermined";
break;
case Algorithm.EnumCategory.Second:
Interpretation = "Negative";
break;
}
dtProductData.Rows.Add(new string[] { ProductName, AvgRating, TopComment, Interpretation, IndividualRating, OutofRating });
}
return(dtProductData);
}
public static DataTable GetDataFromURL(string URL)
{
// Train Dictionary with positive and negative words
Node Positive = Node.CreateMemNodes();
Node Negative = Node.CreateMemNodes();
Dictionary.FillDictionary(Positive, Negative);
// Get Data From Webclient
var url = URL;
clsSerializer objSerializer = new clsSerializer();
var objVenomReviewOverall = objSerializer._download_serialized_json_data<clsJson.Rootobject>(url);
clsJson.Results objRes = new clsJson.Results();
objRes = objVenomReviewOverall.results;
clsJson.Overall[] objOverall; clsJson.Individual[] objIndividual;
objOverall = objRes.Overall; objIndividual = objRes.Individual;
DataTable dtProductData = new DataTable();
dtProductData.Columns.Add("ProductName");
dtProductData.Columns.Add("AverageRating");
dtProductData.Columns.Add("TopComment");
dtProductData.Columns.Add("Interpretation");
dtProductData.Columns.Add("IndividualRating");
dtProductData.Columns.Add("OutofRating");
for (int i = 0; i < objIndividual.Length; i++)
{
string ProductName = objOverall[0].ProductName;
string AvgRating = objOverall[0].AvgRating;
string TopComment = objIndividual[i].TopComment;
string IndividualRating = objIndividual[i].IndividualRating[0];
string TopCommentModified = Dictionary.ModifyInputString(TopComment);
string OutofRating = objIndividual[i].IndividualRating[1];
Algorithm analyzer = new Algorithm(); string Interpretation = "";
Algorithm.EnumCategory result = analyzer.Categorize(Initializer.GetStringsFrom(TopCommentModified), Positive, Negative);
switch (result)
{
case Algorithm.EnumCategory.First:
Interpretation = "Positive";
break;
case Algorithm.EnumCategory.Undetermined:
Interpretation = "Undetermined";
break;
case Algorithm.EnumCategory.Second:
Interpretation = "Negative";
break;
}
dtProductData.Rows.Add(new string[] { ProductName, AvgRating, TopComment, Interpretation, IndividualRating, OutofRating });
}
return dtProductData;
}