/**
* input is a map of artifact.Id and processed text of each artifact
*
*/
public static TLDictionaryIndex build(TLArtifactsCollection setOfProcessedDocuments, ComponentLogger logger)
{
// Variables
TLTermEntry termEntry;
TLPosting posting;
double vectorLength;
// Stores the vector lenght of each document - this is used to normalize the term weights
// The vector length is the square root of the sum of the squares of all the term weights.
Dictionary <string, double> documentVectorLength = new Dictionary <string, double>();
// Creates the dictionary
TLDictionaryIndex dict = new TLDictionaryIndex();
// Iterates over all the documents
foreach (TLArtifact artifact in setOfProcessedDocuments.Values)
{
string[] terms = artifact.Text.Split(new char[] { ' ' }, StringSplitOptions.RemoveEmptyEntries);
if (terms.Length == 0)
{
logger.Warn(String.Format("Artifact Id {0} is empty.", artifact.Id));
}
// Iterates over all the terms
foreach (string t in terms)
{
// Checks if that term has already a posting
if (!dict.ContainsTermEntry(t))
{
// New term
termEntry = dict.AddTermEntry(t, 1, 1, 1.0);
posting = termEntry.AddPosting(artifact.Id, 1, 1.0);
}
else
{
// Existing term
termEntry = dict.GetTermEntry(t);
termEntry.TotalFrequencyAcrossArtifacts += 1;
termEntry.Weight = 1.0;
// Checks if there is already a posting for this document
if (!termEntry.ContainsPosting(artifact.Id))
{
// New posting
termEntry.NumberOfArtifactsContainingTerm += 1;
posting = termEntry.AddPosting(artifact.Id, 1, 1.0);
}
else
{
// Existing posting
posting = termEntry.GetPosting(artifact.Id);
posting.Frequency += 1;
posting.Weight += 1.0;
}
}
}
}
string artId;
// Now that all the counts are in, it calculates the document vector weights
foreach (TLTermEntry t in dict.TermEntries)
{
foreach (TLPosting p in t.Postings)
{
artId = p.ArtifactId;
vectorLength = Math.Pow(p.Frequency, 2);
if (documentVectorLength.ContainsKey(artId))
{
// The document has other terms
vectorLength += documentVectorLength[artId];
}
documentVectorLength[artId] = vectorLength;
}
}
// Finally, we need to get the square root of all entries in the document vector length
foreach (TLArtifact artifact in setOfProcessedDocuments.Values)
{
if (documentVectorLength.ContainsKey(artifact.Id))
{
vectorLength = Math.Sqrt(documentVectorLength[artifact.Id]);
// Here we update the document vector length of the dictionary - not the internal structure any more
dict.SetDocumentVectorWeight(artifact.Id, vectorLength);
}
}
return(dict);
}
/**
* input is a map of artifact.Id and processed text of each artifact
*
*/
public static new TLDictionaryIndex build(TLArtifactsCollection setOfProcessedDocuments, ComponentLogger logger)
{
// Variables
int N = setOfProcessedDocuments.Count; // Total Number of Documents
double idf;
String docId;
double vectorLength;
// Stores the vector lenght of each document - this is used to normalize the term weights
// The vector length is the square root of the sum of the squares of all the term weights.
Dictionary <string, double> documentVectorLength = new Dictionary <string, double>();
// It starts off by calling the parent method, which will calculate the basic frequencies
TLDictionaryIndex dict = BasicIndexBuilder.build(setOfProcessedDocuments, logger);
// Iterates over all the terms
foreach (TLTermEntry term in dict.TermEntries)
{
// Calculates the idf for each term - and stores this in the weight of the term - for weighing queries later
idf = Math.Log10(N / ((double)term.NumberOfArtifactsContainingTerm));
term.Weight = idf;
// Iterates over all the postings
foreach (TLPosting posting in term.Postings)
{
// Multiplies each term weight by the idf
double newWeight = posting.Frequency * idf;
posting.Weight = newWeight;
// Updates the document vector length
docId = posting.ArtifactId;
vectorLength = Math.Pow(newWeight, 2);
if (documentVectorLength.ContainsKey(docId))
{
// The document has other terms
vectorLength += documentVectorLength[docId];
}
documentVectorLength[docId] = vectorLength;
}
}
// Now, we need to get the square root of all entries in the document vector length
foreach (TLArtifact d in setOfProcessedDocuments.Values)
{
docId = d.Id;
if (documentVectorLength.ContainsKey(docId))
{
vectorLength = Math.Sqrt(documentVectorLength[docId]);
documentVectorLength[docId] = vectorLength;
// Here we update the document vector length of the dictionary - not the internal structure anymore
dict.SetDocumentVectorWeight(docId, vectorLength);
}
}
// Lastly, we normalize all the term weights
foreach (TLTermEntry term in dict.TermEntries)
{
foreach (TLPosting posting in term.Postings)
{
vectorLength = documentVectorLength[posting.ArtifactId];
posting.Weight = (posting.Weight / vectorLength);
}
}
return(dict);
}