/// <summary>
/// Computes the similarity for the result object
/// </summary>
/// <param name="result">The result object, previously created with <see cref="Prepare(IEnumerable{HtmlNode}, string, List{string})" /></param>
/// <param name="output">The output.</param>
/// <param name="documents">Optional: select subset of documents to be analysed. These must be within <see cref="result" /> inner collections</param>
/// <returns>
/// The same result object specified in parameters
/// </returns>
public DocumentSimilarityResult ComputeSimilarity(DocumentSimilarityResult result, ITextRender output, List <HtmlNode> documents = null)
{
if (documents.isNullOrEmpty())
{
documents = result.LeafDictionaryByDocuments.Keys.ToList();
}
List <ComputeSimilarityTask> tasks = new List <ComputeSimilarityTask>();
for (int i = 0; i < documents.Count - 1; i++)
{
for (int y = i + 1; y < documents.Count; y++)
{
ComputeSimilarityTask task = new ComputeSimilarityTask()
{
documentA = documents[i],
documentB = documents[y],
nGrams_A = result.NGramsByDocuments[documents[i]],
nGrams_B = result.NGramsByDocuments[documents[y]]
};
tasks.Add(task);
//var documentA = ;
//var documentB = documents[y];
//var ABResult = ComputeSimilarity(documentA, documentB, result);
//result.AddResult(ABResult);
}
}
var task_chunks = tasks.SplitBySize((tasks.Count / 5));
foreach (var task_chunk in task_chunks)
{
output.AppendLine("Executing similarity computation task chunk [size:" + task_chunk.Count + "] " + task_chunks.IndexOf(task_chunk) + " of " + task_chunks.Count);
Parallel.ForEach <ComputeSimilarityTask>(task_chunk, x =>
{
ComputeSimilarity(x);
}
);
foreach (var task in task_chunk)
{
if (task.output != null)
{
result.AddResult(task.output);
}
}
}
return(result);
}
/// <summary>
/// Builds <see cref="LeafNodeDictionary"/> and <see cref="LeafNodeDictionaryEntryNGram"/>s for each document, to allow performance optimization
/// </summary>
/// <param name="documents">The documents.</param>
/// <param name="leafSelectXPath">The leaf select x path, leave blank to use from settings, <see cref="DocumentSimilaritySettings.XPathToSelectLeafs"/></param>
/// <param name="tagsToIgnore">The tags to ignore, leave unspecified to use from settings, <see cref="DocumentSimilaritySettings.TagsToIgnore"/>.</param>
/// <returns></returns>
public DocumentSimilarityResult Prepare(IEnumerable <HtmlNode> documents, String leafSelectXPath = "", List <String> tagsToIgnore = null)
{
leafSelectXPath = leafSelectXPath.or(settings.XPathToSelectLeafs, LeafNodeDictionary.DefaultNodeSelectionXPath);
tagsToIgnore = tagsToIgnore.or(settings.TagsToIgnore, LeafNodeDictionary.DefaultTagsToIgnore);
DocumentSimilarityResult result = new DocumentSimilarityResult();
frequencyCounter <String> xpathCounter = new frequencyCounter <string>();
Dictionary <HtmlNode, LeafNodeDictionary> leafDictionary = new Dictionary <HtmlNode, LeafNodeDictionary>();
foreach (HtmlNode documentA in documents)
{
LeafNodeDictionary leafNodeDictionaryA = new LeafNodeDictionary(documentA, leafSelectXPath, tagsToIgnore);
if (leafNodeDictionaryA.items.Count < 5)
{
}
foreach (var entry in leafNodeDictionaryA.items)
{
xpathCounter.Count(entry.XPath);
}
leafDictionary.Add(documentA, leafNodeDictionaryA);
}
var commonXPaths = xpathCounter.GetItemsWithTopFrequency();
foreach (var pair in leafDictionary)
{
pair.Value.RemoveEntriesByXPath(commonXPaths);
}
foreach (HtmlNode documentA in documents)
{
try
{
LeafNodeDictionary leafNodeDictionaryA = leafDictionary[documentA];
List <LeafNodeDictionaryEntryNGram> nGrams_A = setAnalysisTools <LeafNodeDictionaryEntry> .getNGramSet <LeafNodeDictionaryEntryNGram>(leafNodeDictionaryA.items, settings.nGramWidth, settings.nGramMode);
result.DocumentsByLeafDictionary.Add(leafNodeDictionaryA, documentA);
result.DocumentsByNGrams.Add(nGrams_A, documentA);
result.LeafDictionaryByDocuments.Add(documentA, leafNodeDictionaryA);
result.NGramsByDocuments.Add(documentA, nGrams_A);
} catch (Exception ex)
{
result.DocumentsWithExceptions.Add(documentA, ex);
}
}
return(result);
}
/// <summary>
/// Computes similarity for two documents, that are part of result's inner collections
/// </summary>
/// <param name="documentA">The document a.</param>
/// <param name="documentB">The document b.</param>
/// <param name="result">The result object, previously created with <see cref="Prepare(IEnumerable{HtmlNode}, string, List{string})"/></param>
/// <returns>Result for these two documents</returns>
public DocumentSimilarityResultPair ComputeSimilarity(HtmlNode documentA, HtmlNode documentB, DocumentSimilarityResult result)
{
List <LeafNodeDictionaryEntryNGram> nGrams_A = result.NGramsByDocuments[documentA]; //setAnalysisTools<LeafNodeDictionaryEntry>.getNGramSet<LeafNodeDictionaryEntryNGram>(leafNodeDictionaryA.items, settings.nGramWidth, settings.nGramMode);
List <LeafNodeDictionaryEntryNGram> nGrams_B = result.NGramsByDocuments[documentB]; //setAnalysisTools<LeafNodeDictionaryEntry>.getNGramSet<LeafNodeDictionaryEntryNGram>(leafNodeDictionaryB.items, settings.nGramWidth, settings.nGramMode);
var score_StructureSimilarity = StructureSimilarity.GetSimilarity(nGrams_A, nGrams_B, settings.computationMethod);
var score_ContentSimilarity = ContentSimilarity.GetSimilarity(nGrams_A, nGrams_B, settings.computationMethod);
DocumentSimilarityResultPair output = new DocumentSimilarityResultPair
{
itemA = documentA,
itemB = documentB,
StructureSimilarity = score_StructureSimilarity,
ContentSimilarity = score_ContentSimilarity
};
return(output);
}