/// <summary>
/// Instructs HTML to text extraction engine (EntityPlaneMethod) to produce text from xpath
/// </summary>
/// <param name="name">Instruction name, it is human-readable descriptive name or special instructin name like ::BODYTEXT::</param>
/// <param name="flags">The flags.</param>
/// <param name="code">XPath associated with the instruction, selects nodes to be rendered into text</param>
/// <param name="weight">Weight factor of the instruction, i.e. number of times the content should be repeated (boosting TF)</param>
/// <param name="expansion">The expansion.</param>
/// <param name="remove">if set to <c>true</c> [remove].</param>
/// <remarks>
/// It will add specified instruction to the rendering instruction set, and optionally remove all existing instructions before it.
/// </remarks>
/// <seealso cref="aceOperationSetExecutorBase" />
public void aceOperation_setRenderInstruction(
[Description("Instruction name, it is human-readable descriptive name or special instructin name like ::BODYTEXT::")] String name = "::BODYTEXT::",
[Description("Instruction flags, controls what and how to render")] DocumentRenderInstructionFlags flags = DocumentRenderInstructionFlags.this_page_content,
[Description("XPath associated with the instruction, selects nodes to be rendered into text")] String code = "",
[Description("Weight factor of the instruction, i.e. number of times the content should be repeated (boosting TF)")] Double weight = 1.0,
[Description("Graph selection expansion steps - to reach 1+ edges far nodes ")] Int32 expansion = 1,
[Description("If true it will remove any existing instruction in the set")] Boolean remove = false)
{
if (remove)
{
data.instructions.Clear();
}
DocumentRenderInstruction dri = new DocumentRenderInstruction(name, code, weight);
dri.instructionFlags = flags;
dri.graphExpansionSteps = expansion;
dri.weight = weight;
data.instructions.Add(dri);
}
/// <summary>
/// Gets default configuration
/// </summary>
/// <returns></returns>
public static PlanesMethodSettings GetDefaultSettings()
{
PlanesMethodSettings output = new PlanesMethodSettings();
output.entityMethod.instructions.Add(DocumentRenderInstruction.GetDescriptionInstruction());
output.entityMethod.instructions.Add(DocumentRenderInstruction.GetTitleInstruction());
output.entityMethod.instructions.Add(DocumentRenderInstruction.GetBodyTextInstruction());
// output.entityMethod.blenderOptions = DocumentBlenderFunctionOptions.binaryAggregation | DocumentBlenderFunctionOptions.pageLevel;
output.entityMethod.filterFunctionName = ""; // nameof(DocumentEntropyFunction);
output.entityMethod.filterLimit = 5;
output.corpusMethod.stemmer = nameof(EnglishStemmer);
output.corpusMethod.tokenizer = nameof(TokenizerBasic);
output.corpusMethod.transliterationRuleSetId = "";
#region PREPARE Weighting model
var weightModel = new FeatureWeightModel();
weightModel.LocalFunction = new Weighting.Local.TermFrequencyFunction();
var globalFactor = new FeatureWeightFactor();
globalFactor.Settings.functionName = nameof(IDFElement);
weightModel.GlobalFactors.Add(globalFactor);
output.corpusMethod.WeightModel = weightModel;
#endregion
var featureFilter = new FeatureFilter();
featureFilter.limit = 8000;
//featureFilter.
//featureFilter.functionSettings = new GlobalFunctionSettings();
//featureFilter.functionSettings.functionName = nameof(CollectionTDPElement);
//featureFilter.functionSettings.weight = 1.0;
//featureFilter.functionSettings.flags.Add(Weighting.Metrics.TDPFactor.chi.ToString());
output.corpusMethod.filter = featureFilter;
/*
* output.vectorMethod.constructor = new Feature.Settings.FeatureVectorConstructorSettings();
* dimensionSpecification dimSpec = new dimensionSpecification();
* dimSpec.functionName = nameof(CosineSimilarityFunction);
* dimSpec.type = FeatureVectorDimensionType.similarityFunction;
* output.vectorMethod.constructor.labelDimensions.Add(dimSpec);
*/
//output.vectorMethod.constructor = new Feature.Settings.FeatureVectorConstructorSettings();
//dimensionSpecification dimSpec = new dimensionSpecification();
////dimSpec.functionName = nameof(CosineSimilarityFunction);
//dimSpec.type = FeatureVectorDimensionType.directTermWeight;
//output.vectorMethod.constructor.featureDimensions.Add(dimSpec);
output.featureMethod.classifierSettings.type = Classifiers.ClassifierType.multiClassSVM;
output.featureMethod.classifierSettings.lossFunctionForTraining = Accord.MachineLearning.VectorMachines.Learning.Loss.L2;
/*
* output.featureMethod.classifierSettings.type = Classifiers.ClassifierType.kNearestNeighbors;
* output.featureMethod.classifierSettings.lossFunctionForTraining = Accord.MachineLearning.VectorMachines.Learning.Loss.L2;
* output.featureMethod.classifierSettings.kNN_k = 4;
*/
return(output);
}
