| Modifier and Type | Method and Description |
|---|---|
IRDoc |
DocClass.getDoc(int index) |
| Modifier and Type | Method and Description |
|---|---|
boolean |
DocClassSet.addDoc(int classID,
IRDoc curDoc) |
boolean |
DocClass.addDoc(IRDoc doc) |
int |
NigamActiveLearning.classify(IRDoc curDoc) |
int |
NBClassifier.classify(IRDoc doc) |
int |
Classifier.classify(IRDoc doc)
Classify one particular document
|
int |
AbstractClassifier.classify(IRDoc doc) |
boolean |
DocClass.contains(IRDoc curDoc) |
| Modifier and Type | Method and Description |
|---|---|
IRDoc |
DocCluster.getDoc(int index) |
| Modifier and Type | Method and Description |
|---|---|
boolean |
DocClusterSet.addDoc(int clusterID,
IRDoc curDoc) |
boolean |
DocCluster.addDoc(IRDoc doc) |
boolean |
LinkKMean.cluster(IRDoc[] arrDoc) |
boolean |
HierClustering.cluster(IRDoc[] arrDoc) |
boolean |
Clustering.cluster(IRDoc[] arrDoc)
Cluster given testing documents to the given number of clusters
|
boolean |
BisectKMean.cluster(IRDoc[] arrDoc) |
boolean |
BasicKMean.cluster(IRDoc[] arrDoc) |
boolean |
DocCluster.containDoc(IRDoc doc) |
protected DoubleDenseMatrix |
LinkKMean.estimateClassTransferProb(IRDoc[] arrDoc,
int[] arrDocLabel) |
protected double |
LinkKMean.getLogLikelihood(IRDoc doc,
int clusterID,
DoubleDenseMatrix transMatrix,
double[] arrOutLinks,
double[] arrInLinks) |
protected boolean |
LinkKMean.initialize(IRDoc[] arrDoc) |
protected boolean |
BasicKMean.initialize(IRDoc[] arrDoc) |
boolean |
DocClusterSet.removeDoc(int clusterID,
IRDoc curDoc) |
boolean |
DocCluster.removeDoc(IRDoc doc) |
| Modifier and Type | Method and Description |
|---|---|
double |
ClusterModel.getDistance(IRDoc doc,
DocCluster cluster) |
double |
AbstractClusterModel.getDistance(IRDoc doc,
DocCluster cluster) |
double |
MultinomialClusterModel.getDistance(IRDoc doc,
int clusterID) |
double |
EuclideanClusterModel.getDistance(IRDoc doc,
int clusterID) |
double |
CosineClusterModel.getDistance(IRDoc doc,
int clusterID) |
double |
ClusterModel.getDistance(IRDoc doc,
int clusterNo) |
| Modifier and Type | Method and Description |
|---|---|
double |
KLDivDocDistance.getDistance(IRDoc first,
IRDoc second) |
double |
EuclideanDocDistance.getDistance(IRDoc first,
IRDoc second) |
double |
DocDistance.getDistance(IRDoc first,
IRDoc second) |
double |
CosineDocDistance.getDistance(IRDoc first,
IRDoc second) |
| Modifier and Type | Method and Description |
|---|---|
protected int[] |
NullFeatureFilter.getSelectedFeatures(IndexReader indexReader,
IRDoc[] docSet) |
protected int[] |
DocFrequencyFilter.getSelectedFeatures(IndexReader indexReader,
IRDoc[] docSet) |
protected abstract int[] |
AbstractFeatureFilter.getSelectedFeatures(IndexReader indexReader,
IRDoc[] docSet) |
void |
FeatureFilter.initialize(IndexReader indexReader,
IRDoc[] docSet)
This method chooses a subset of features for text clustering
|
void |
AbstractFeatureFilter.initialize(IndexReader indexReader,
IRDoc[] docSet) |
| Modifier and Type | Method and Description |
|---|---|
IRDoc |
IRDoc.copy() |
IRDoc |
OnlineIRDocIndexList.get(int index) |
IRDoc |
IRDocIndexList.get(int index)
Gets the IRDoc specified by its index
|
IRDoc |
BasicIRDocIndexList.get(int index) |
IRDoc |
IndexReader.getDoc(int index) |
IRDoc |
AbstractIndexReader.getDoc(int index) |
IRDoc |
IndexReader.getDoc(String key) |
IRDoc |
AbstractIndexReader.getDoc(String key) |
IRDoc[] |
IndexReader.getRelationDocList(int relationIndex) |
IRDoc[] |
AbstractIndexReader.getRelationDocList(int relationIndex) |
IRDoc[] |
IndexReader.getTermDocList(int termIndex) |
IRDoc[] |
AbstractIndexReader.getTermDocList(int termIndex) |
| Modifier and Type | Method and Description |
|---|---|
boolean |
OnlineIRDocIndexList.add(IRDoc curDoc) |
boolean |
IRDocIndexList.add(IRDoc curDoc)
Adds an IRDoc object to the index list
|
boolean |
BasicIRDocIndexList.add(IRDoc curDoc) |
int |
IRDoc.compareTo(IRDoc doc) |
protected IRRelation[] |
AbstractIndexWriteController.getIRRelationArray(ArrayList irRelationList,
IRDoc curDoc) |
protected IRTerm[] |
AbstractIndexWriteController.getIRTermArray(ArrayList irtermList,
IRDoc curDoc) |
boolean |
IndexWriter.write(IRDoc curDoc,
IRTerm[] arrTerms)
All fields (doc key, doc index, term count, term number, relation count, and relation number) of the IRDoc object should be set.
|
boolean |
AbstractIndexWriter.write(IRDoc curDoc,
IRTerm[] arrTerms) |
boolean |
IndexWriter.write(IRDoc curDoc,
IRTerm[] arrTerms,
IRRelation[] arrRelations)
All fields (doc key, doc index, term count, term number, relation count, and relation number) of the IRDoc object should be set.
|
boolean |
AbstractIndexWriter.write(IRDoc curDoc,
IRTerm[] arrTerms,
IRRelation[] arrRelations) |
| Modifier and Type | Method and Description |
|---|---|
IRDoc |
AbstractSequenceIndexReader.getDoc(int index) |
IRDoc |
AbstractSequenceIndexReader.getDoc(String key) |
IRDoc[] |
AbstractSequenceIndexReader.getRelationDocList(int relationIndex) |
IRDoc[] |
AbstractSequenceIndexReader.getTermDocList(int termIndex) |
| Modifier and Type | Method and Description |
|---|---|
boolean |
AbstractSequenceIndexWriter.write(IRDoc curDoc,
IRTerm[] arrTerm) |
boolean |
AbstractSequenceIndexWriter.write(IRDoc curDoc,
IRTerm[] arrTerms,
IRRelation[] arrRelations) |
| Modifier and Type | Method and Description |
|---|---|
IRDoc |
Searcher.getIRDoc(int ranking)
Before calling this method, one should call the search function.
|
IRDoc |
AbstractSearcher.getIRDoc(int ranking) |
| Modifier and Type | Method and Description |
|---|---|
protected IRDoc |
AbstractMixtureWeightEM.getDoc(int seq) |
| Modifier and Type | Method and Description |
|---|---|
protected void |
DocTransMixtureWeightEM.getComponentValue(IRDoc curDoc,
int freq,
double[] arrComp) |
protected abstract void |
AbstractMixtureWeightEM.getComponentValue(IRDoc curDoc,
int freq,
double[] componentProbs) |
double |
Smoother.getSmoothedProb(IRDoc doc)
It is equal to calling getSmoothedProb(doc, 0);
|
double |
AbstractSmoother.getSmoothedProb(IRDoc doc) |
double |
Smoother.getSmoothedProb(IRDoc doc,
int termFreq)
Before calling this method, one should call the setQueryTerm method.
|
double |
AbstractSmoother.getSmoothedProb(IRDoc doc,
int termFreq) |
double |
Smoother.getSmoothedProb(IRDoc doc,
SimpleTermPredicate queryTerm)
This method is equal to call getSmoothedProb(doc, queryTerm, 0).
|
double |
AbstractSmoother.getSmoothedProb(IRDoc doc,
SimpleTermPredicate queryTerm) |
double |
Smoother.getSmoothedProb(IRDoc doc,
SimpleTermPredicate queryTerm,
int termFreq) |
double |
AbstractSmoother.getSmoothedProb(IRDoc doc,
SimpleTermPredicate queryTerm,
int termFreq) |
void |
TwoStageSmoother.setDoc(IRDoc doc) |
void |
TFIDFSmoother.setDoc(IRDoc doc) |
void |
Smoother.setDoc(IRDoc doc)
Set the current document for processing
|
void |
QueryFirstTransSmoother.setDoc(IRDoc doc) |
void |
PivotedNormSmoother.setDoc(IRDoc doc) |
void |
OkapiSmoother.setDoc(IRDoc doc) |
void |
JMSmoother.setDoc(IRDoc doc) |
protected void |
DocTransMixtureWeightEM.setDoc(IRDoc curDoc) |
void |
DocFirstTransSmoother.setDoc(IRDoc curDoc) |
void |
DirichletSmoother.setDoc(IRDoc doc) |
protected abstract void |
AbstractMixtureWeightEM.setDoc(IRDoc doc) |
void |
AbsoluteDiscountSmoother.setDoc(IRDoc doc) |
protected void |
DocTransMixtureWeightEM.setInitialParameters(double[] arrCoefficient,
IRDoc[] arrDoc) |
protected abstract void |
AbstractMixtureWeightEM.setInitialParameters(double[] arrCoefficient,
IRDoc[] arrDoc) |
| Modifier and Type | Method and Description |
|---|---|
protected double |
SemanticRankSummarizer.computeSimilarity(IRDoc firstSent,
IRDoc secondSent) |
protected double |
LexRankSummarizer.computeSimilarity(IRDoc firstSent,
IRDoc secondSent)
LexRank Summarizer uses cosine similrity.
|
protected double |
ClusterLexRankSummarizer.computeSimilarity(IRDoc firstSent,
IRDoc secondSent) |
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