A B C D E F G I L M N O P R S T V W
All Classes All Packages

A

ABCFormat - Interface in org.nlpub.watset.util

Utilities for handling the ABC (source, target, weight) edge list format.

AlgorithmProvider<V,E> - Class in org.nlpub.watset.util

A utility class that creates instances of the graph clustering algorithms.

AlgorithmProvider(String) - Constructor for class org.nlpub.watset.util.AlgorithmProvider

Create an instance of this utility class with empty parameter map.

AlgorithmProvider(String, Map<String, String>) - Constructor for class org.nlpub.watset.util.AlgorithmProvider

Create an instance of this utility class.

alwaysFalse() - Static method in interface org.nlpub.watset.util.Maximizer

A predicate that is always false.

alwaysTrue() - Static method in interface org.nlpub.watset.util.Maximizer

A predicate that is always true.

Application - Class in org.nlpub.watset.cli

Watset command-line interface.

Application() - Constructor for class org.nlpub.watset.cli.Application

apply(Map<V, Number>, Map<V, Number>) - Method in class org.nlpub.watset.util.ContextSimilarity.DummyContextSimilarity

apply(Map<V, Number>, Map<V, Number>) - Method in class org.nlpub.watset.util.CosineContextSimilarity

apply(Graph<V, E>) - Method in class org.nlpub.watset.util.AlgorithmProvider

apply(Graph<V, E>, Map<V, Integer>, V, V) - Method in interface org.nlpub.watset.graph.NodeWeighting

Compute the weight of the node in the neighborhood graph.

apply(Graph<V, E>, Map<V, Integer>, V, V) - Method in class org.nlpub.watset.graph.NodeWeighting.LabelNodeWeighting

apply(Graph<V, E>, Map<V, Integer>, V, V) - Method in class org.nlpub.watset.graph.NodeWeighting.LinearNodeWeighting

apply(Graph<V, E>, Map<V, Integer>, V, V) - Method in class org.nlpub.watset.graph.NodeWeighting.LogNodeWeighting

apply(Graph<V, E>, Map<V, Integer>, V, V) - Method in class org.nlpub.watset.graph.NodeWeighting.TopNodeWeighting

argmax(Iterator<V>, Function<V, S>) - Static method in interface org.nlpub.watset.util.Maximizer

Find the first argument of the maximum (argmax) of the function.

argmax(Iterator<V>, Predicate<V>, Function<V, S>) - Static method in interface org.nlpub.watset.util.Maximizer

Find the first argument of the maximum (argmax) of the function.

argmaxRandom(Iterator<V>, Function<V, S>, Random) - Static method in interface org.nlpub.watset.util.Maximizer

Find the arguments of the maxima (argmax) of the function and randomly choose any of them.

B

buildIndex() - Method in class org.nlpub.watset.graph.MarkovClustering

Index the nodes of the input graph.

buildMatrix(Map<V, Integer>) - Method in class org.nlpub.watset.graph.MarkovClustering

Construct an adjacency matrix for the given graph.

C

cache - Variable in class org.nlpub.watset.eval.CachedNormalizedModifiedPurity

The cache.

CachedNormalizedModifiedPurity<V> - Class in org.nlpub.watset.eval

Cached normalized modified purity evaluation measure for overlapping clustering.

CachedNormalizedModifiedPurity() - Constructor for class org.nlpub.watset.eval.CachedNormalizedModifiedPurity

Construct a cached normalized modified purity calculator.

CachedNormalizedModifiedPurity(boolean, boolean) - Constructor for class org.nlpub.watset.eval.CachedNormalizedModifiedPurity

Construct a cached normalized modified purity calculator that allows turning normalized and/or modified options off.

ChineseWhispers<V,E> - Class in org.nlpub.watset.graph

Implementation of the Chinese Whispers algorithm.

ChineseWhispers(Graph<V, E>, NodeWeighting<V, E>) - Constructor for class org.nlpub.watset.graph.ChineseWhispers

Create an instance of the Chinese Whispers algorithm.

ChineseWhispers(Graph<V, E>, NodeWeighting<V, E>, int, Random) - Constructor for class org.nlpub.watset.graph.ChineseWhispers

Create an instance of the Chinese Whispers algorithm.

Clustering<V> - Interface in org.nlpub.watset.graph

An instance of Clustering returns clusters after running the underlying algorithm.

clusters(V) - Method in class org.nlpub.watset.graph.SenseInduction

Get the induced sense clusters.

combination(Collection<V>) - Static method in class org.nlpub.watset.eval.Pairwise

Return a stream of pairs generated as 2-combinations of the cluster elements.

Command - Class in org.nlpub.watset.cli

A generic command of the Watset command-line interface.

Command() - Constructor for class org.nlpub.watset.cli.Command

Command.Parameters - Class in org.nlpub.watset.cli

Watset command-line interface parameters.

ComponentsClustering<V,E> - Class in org.nlpub.watset.graph

A trivial clustering algorithm that treats every connected component as a cluster.

ComponentsClustering(Graph<V, E>) - Constructor for class org.nlpub.watset.graph.ComponentsClustering

Set up the trivial clustering algorithm that treats every connected component as a cluster.

contexts(V) - Method in class org.nlpub.watset.graph.SenseInduction

Get the induced senses and their non-disambiguated contexts.

ContextSimilarity<V> - Interface in org.nlpub.watset.util

A similarity measure between two bags-of-words that maps them to a number.

ContextSimilarity.DummyContextSimilarity<V> - Class in org.nlpub.watset.util

A simple context similarity measure that always returns zero.

convert(String) - Method in class org.nlpub.watset.cli.PathConverter

CosineContextSimilarity<V> - Class in org.nlpub.watset.util

The classical cosine similarity measure for bags-of-words.

CosineContextSimilarity() - Constructor for class org.nlpub.watset.util.CosineContextSimilarity

D

DELIMITER - Static variable in interface org.nlpub.watset.util.ILEFormat

The default delimiter, expressed by comma and space.

delta(Map<V, Double>, Map<V, Double>) - Method in class org.nlpub.watset.eval.NormalizedModifiedPurity

Compute the fuzzy overlap between two clusters, cluster and klass.

disambiguate(Map<V, Map<Sense<V>, Map<V, Number>>>, ContextSimilarity<V>, Map<V, Number>, Collection<V>) - Static method in interface org.nlpub.watset.util.Sense

Disambiguate each element of the context by maximizing its similarity to the senses in the inventory.

DummyContextSimilarity() - Constructor for class org.nlpub.watset.util.ContextSimilarity.DummyContextSimilarity

E

e - Variable in class org.nlpub.watset.graph.MarkovClustering

The expansion parameter.

EmptyClustering<V> - Class in org.nlpub.watset.graph

A trivial clustering algorithm that returns no clusters.

EmptyClustering() - Constructor for class org.nlpub.watset.graph.EmptyClustering

Set up the empty clustering algorithm.

evaluate(Collection<Collection<V>>, Collection<Collection<V>>) - Method in class org.nlpub.watset.eval.Pairwise

Compute a pairwise precision, recall, and F-score.

evaluate(NormalizedModifiedPurity<V>, NormalizedModifiedPurity<V>, Collection<Map<V, Double>>, Collection<Map<V, Double>>) - Static method in class org.nlpub.watset.eval.NormalizedModifiedPurity

Compute a precision and recall using purity and inverse purity, correspondingly.

expand() - Method in class org.nlpub.watset.graph.MarkovClustering

Perform the expansion step.

F

fit() - Method in class org.nlpub.watset.graph.ChineseWhispers

fit() - Method in interface org.nlpub.watset.graph.Clustering

Run the algorithm to induce the parameters of the clusters.

fit() - Method in class org.nlpub.watset.graph.ComponentsClustering

fit() - Method in class org.nlpub.watset.graph.EmptyClustering

fit() - Method in class org.nlpub.watset.graph.MarkovClustering

fit() - Method in class org.nlpub.watset.graph.MarkovClusteringBinaryRunner

fit() - Method in class org.nlpub.watset.graph.MaxMax

fit() - Method in class org.nlpub.watset.graph.SimplifiedWatset

fit() - Method in class org.nlpub.watset.graph.SingletonClustering

fit() - Method in class org.nlpub.watset.graph.TogetherClustering

fit() - Method in class org.nlpub.watset.graph.Watset

Deprecated.

G

get() - Method in class org.nlpub.watset.util.IndexedSense

getClusters() - Method in class org.nlpub.watset.eval.Measurer

Return the list of the measured number of clusters.

getClusters() - Method in class org.nlpub.watset.graph.ChineseWhispers

getClusters() - Method in interface org.nlpub.watset.graph.Clustering

Return a collection of clusters, each cluster is a collection of objects.

getClusters() - Method in class org.nlpub.watset.graph.ComponentsClustering

getClusters() - Method in class org.nlpub.watset.graph.EmptyClustering

getClusters() - Method in class org.nlpub.watset.graph.MarkovClustering

getClusters() - Method in class org.nlpub.watset.graph.MarkovClusteringBinaryRunner

getClusters() - Method in class org.nlpub.watset.graph.MaxMax

getClusters() - Method in class org.nlpub.watset.graph.SimplifiedWatset

getClusters() - Method in class org.nlpub.watset.graph.SingletonClustering

getClusters() - Method in class org.nlpub.watset.graph.TogetherClustering

getClusters() - Method in class org.nlpub.watset.graph.Watset

Deprecated.

getContexts() - Method in class org.nlpub.watset.graph.SimplifiedWatset

Get the disambiguated contexts built during SimplifiedWatset.fit().

getContexts() - Method in class org.nlpub.watset.graph.Watset

Deprecated.

Get the disambiguated contexts built during Watset.fit().

getDigraph() - Method in class org.nlpub.watset.graph.MaxMax

Return the directed graph representation of the input graph.

getDurations() - Method in class org.nlpub.watset.eval.Measurer

Return the list of the measured graph clustering durations in milliseconds.

getF1Score() - Method in class org.nlpub.watset.eval.PrecisionRecall

Compute the F₁-score using precision and recall.

getFScore(double) - Method in class org.nlpub.watset.eval.PrecisionRecall

Compute the F_β-score using precision and recall.

getGraph() - Method in class org.nlpub.watset.cli.Command

Read, parse, and return the input graph stored in Command.Parameters.input.

getGraph() - Method in class org.nlpub.watset.eval.Measurer

Return the input graph.

getInventory() - Method in class org.nlpub.watset.graph.Watset

Deprecated.

Get the sense inventory built during Watset.fit().

getIterations() - Method in class org.nlpub.watset.graph.ChineseWhispers

Return the number of iterations specified in the constructor

getMaximals() - Method in class org.nlpub.watset.graph.MaxMax

Return the map of nodes to their maximal affinity nodes.

getPrecision() - Method in class org.nlpub.watset.eval.PrecisionRecall

Get the value of precision.

getRecall() - Method in class org.nlpub.watset.eval.PrecisionRecall

Get the value of recall.

getRoots() - Method in class org.nlpub.watset.graph.MaxMax

Return the map of root and non-root nodes.

getSense() - Method in class org.nlpub.watset.util.IndexedSense

Get the sense identifier.

getSenseGraph() - Method in class org.nlpub.watset.graph.SimplifiedWatset

Get the intermediate node sense graph built during SimplifiedWatset.fit().

getSenseGraph() - Method in class org.nlpub.watset.graph.Watset

Deprecated.

Get the intermediate node sense graph built during Watset.fit().

getSteps() - Method in class org.nlpub.watset.graph.ChineseWhispers

Return the number of iterations actually performed during ChineseWhispers.fit().

graph - Variable in class org.nlpub.watset.graph.ChineseWhispers

The graph.

graph - Variable in class org.nlpub.watset.graph.MarkovClustering

The graph.

I

ILEFormat - Interface in org.nlpub.watset.util

Utilities for handling the ILE (identifier, length, elements) file format.

index - Variable in class org.nlpub.watset.graph.MarkovClustering

The mapping of graph nodes to the columns of matrix.

IndexedSense<V> - Class in org.nlpub.watset.util

An integer sense identifier.

IndexedSense(V, Integer) - Constructor for class org.nlpub.watset.util.IndexedSense

Create a sense of an object.

inflate() - Method in class org.nlpub.watset.graph.MarkovClustering

Perform the inflation step.

inflateVisitor - Variable in class org.nlpub.watset.graph.MarkovClustering

The inflation visitor that raises each element of matrix to the power of r.

input - Variable in class org.nlpub.watset.cli.Command.Parameters

The input file.

iterations - Variable in class org.nlpub.watset.graph.ChineseWhispers

The number of iterations.

ITERATIONS - Static variable in class org.nlpub.watset.graph.ChineseWhispers

The default number of Chinese Whispers iterations.

ITERATIONS - Static variable in class org.nlpub.watset.graph.MarkovClustering

The default number of Markov Clustering iterations.

L

label() - Static method in interface org.nlpub.watset.graph.NodeWeighting

A static factory method providing a convenient way to create an instance of LabelNodeWeighting.

LabelNodeWeighting() - Constructor for class org.nlpub.watset.graph.NodeWeighting.LabelNodeWeighting

labels - Variable in class org.nlpub.watset.graph.ChineseWhispers

The mapping of nodes to labels.

linear() - Static method in interface org.nlpub.watset.graph.NodeWeighting

A static factory method providing a convenient way to create an instance of LinearNodeWeighting.

LinearNodeWeighting() - Constructor for class org.nlpub.watset.graph.NodeWeighting.LinearNodeWeighting

load(ClassDict) - Static method in interface org.nlpub.watset.util.NetworkXFormat

Reconstruct a Graph object from the unpickled NetworkX graph.

log() - Static method in interface org.nlpub.watset.graph.NodeWeighting

A static factory method providing a convenient way to create an instance of LogNodeWeighting.

LogNodeWeighting() - Constructor for class org.nlpub.watset.graph.NodeWeighting.LogNodeWeighting

M

main(String[]) - Static method in class org.nlpub.watset.cli.Application

Watset Command-Line Interface Entry Point.

MarkovClustering<V,E> - Class in org.nlpub.watset.graph

Naïve implementation of the Markov Clustering (MCL) algorithm.

MarkovClustering(Graph<V, E>, int, double) - Constructor for class org.nlpub.watset.graph.MarkovClustering

Create an instance of the Markov Clustering algorithm.

MarkovClustering.InflateVisitor - Class in org.nlpub.watset.graph

Visitor that raises each element to the power of MarkovClustering.r.

MarkovClustering.NormalizeVisitor - Class in org.nlpub.watset.graph

Visitor that normalizes columns.

MarkovClusteringBinaryRunner<V,E> - Class in org.nlpub.watset.graph

A wrapper for the official implementation of the Markov Clustering (MCL) algorithm in C.

MarkovClusteringBinaryRunner(Graph<V, E>, Path, double) - Constructor for class org.nlpub.watset.graph.MarkovClusteringBinaryRunner

Create an instance of the Markov Clustering algorithm wrapper.

MarkovClusteringBinaryRunner(Graph<V, E>, Path, double, int) - Constructor for class org.nlpub.watset.graph.MarkovClusteringBinaryRunner

Create an instance of the Markov Clustering algorithm wrapper.

matrix - Variable in class org.nlpub.watset.graph.MarkovClustering

The stochastic matrix.

Maximizer - Interface in org.nlpub.watset.util

Utilities for searching arguments of the maxima of the function.

MaxMax<V,E> - Class in org.nlpub.watset.graph

Implementation of the MaxMax soft clustering algorithm.

MaxMax(Graph<V, E>) - Constructor for class org.nlpub.watset.graph.MaxMax

Create an instance of the MaxMax algorithm.

Measurer<V,E> - Class in org.nlpub.watset.eval

A clustering algorithm performance measurement class.

Measurer(Function<Graph<V, E>, Clustering<V>>, Graph<V, E>) - Constructor for class org.nlpub.watset.eval.Measurer

Create an instance of Measurer.

Measurer(Function<Graph<V, E>, Clustering<V>>, Graph<V, E>, int, int) - Constructor for class org.nlpub.watset.eval.Measurer

Create an instance of Measurer.

N

neighborhoodGraph(Graph<V, E>, V) - Static method in interface org.nlpub.watset.util.Neighbors

Create an iterator over the neighbors of the given node.

neighborIterator(Graph<V, E>, V) - Static method in interface org.nlpub.watset.util.Neighbors

Create an iterator over the neighbors of the given node.

Neighbors - Interface in org.nlpub.watset.util

Utilities for extracting neighborhood graphs and iterating over them.

neighborSetOf(Graph<V, E>, V) - Static method in interface org.nlpub.watset.util.Neighbors

Extract the neighbors of the given node.

NetworkXFormat - Interface in org.nlpub.watset.util

Utilities for handling pickled NetworkX graphs.

newInputStream() - Method in class org.nlpub.watset.cli.Command

Provide a stream to the input file.

newOutputWriter() - Method in class org.nlpub.watset.cli.Command

Provide a writer to the output file.

NodeWeighting<V,E> - Interface in org.nlpub.watset.graph

Node weighting for Chinese Whispers.

NodeWeighting.LabelNodeWeighting<V,E> - Class in org.nlpub.watset.graph

A trivial and not particularly useful node weighting approach that assigns the current node label as the weight.

NodeWeighting.LinearNodeWeighting<V,E> - Class in org.nlpub.watset.graph

The node weighting approach that chooses the label with the highest total edge weight in the neighborhood divided by the neighbor node degree.

NodeWeighting.LogNodeWeighting<V,E> - Class in org.nlpub.watset.graph

The node weighting approach that chooses the label with the highest total edge weight in the neighborhood divided by the logarithm of the neighbor node degree.

NodeWeighting.TopNodeWeighting<V,E> - Class in org.nlpub.watset.graph

The node weighting approach that chooses the label with the highest total edge weight in the neighborhood.

normalize() - Method in class org.nlpub.watset.graph.MarkovClustering

Normalize the matrix.

normalize(Collection<Map<V, Double>>) - Static method in class org.nlpub.watset.eval.NormalizedModifiedPurity

Normalize weights of the cluster elements to allow using normalized (modified) purity.

NormalizedModifiedPurity<V> - Class in org.nlpub.watset.eval

Normalized modified purity evaluation measure for overlapping clustering.

NormalizedModifiedPurity() - Constructor for class org.nlpub.watset.eval.NormalizedModifiedPurity

Construct a normalized modified purity calculator.

NormalizedModifiedPurity(boolean, boolean) - Constructor for class org.nlpub.watset.eval.NormalizedModifiedPurity

Construct a normalized modified purity calculator that allows turning normalized and/or modified options off.

NormalizeVisitor(RealMatrix) - Constructor for class org.nlpub.watset.graph.MarkovClustering.NormalizeVisitor

Create an instance of the normalizer.

O

ones - Variable in class org.nlpub.watset.graph.MarkovClustering

The row matrix filled by ones.

org.nlpub.watset.cli - package org.nlpub.watset.cli

Command-line interface.

org.nlpub.watset.eval - package org.nlpub.watset.eval

Clustering and performance evaluation tools.

org.nlpub.watset.graph - package org.nlpub.watset.graph

Graph processing and clustering.

org.nlpub.watset.util - package org.nlpub.watset.util

Utility classes and helpers.

output - Variable in class org.nlpub.watset.cli.Command.Parameters

The output file.

P

pairOf(V, V) - Static method in class org.nlpub.watset.eval.Pairwise

Create a pair of elements ordered by hashCode.

Pairwise<V> - Class in org.nlpub.watset.eval

Pairwise precision, recall, and F-score for cluster evaluation.

Pairwise() - Constructor for class org.nlpub.watset.eval.Pairwise

Create an instance of pairwise precision and recall calculator.

parameters - Variable in class org.nlpub.watset.cli.Command

The command-line parameters.

Parameters() - Constructor for class org.nlpub.watset.cli.Command.Parameters

parse(InputStream) - Static method in interface org.nlpub.watset.util.NetworkXFormat

Unpickle the NetworkX graph from the input stream.

parse(Stream<String>) - Static method in interface org.nlpub.watset.util.ABCFormat

Parse the string stream of ABC-formatted edges.

parse(Stream<String>, String) - Static method in interface org.nlpub.watset.util.ABCFormat

Parse the string stream of ABC-formatted edges.

PathConverter - Class in org.nlpub.watset.cli

An interface that converts strings to Path.

PathConverter() - Constructor for class org.nlpub.watset.cli.PathConverter

PrecisionRecall - Class in org.nlpub.watset.eval

A wrapper for precision and recall values that computes F-score.

PrecisionRecall(double, double) - Constructor for class org.nlpub.watset.eval.PrecisionRecall

Wrap the precision and recall values.

provider() - Static method in class org.nlpub.watset.graph.EmptyClustering

A factory function that sets up the algorithm for the given graph.

provider() - Static method in class org.nlpub.watset.graph.MaxMax

A factory function that sets up the algorithm for the given graph.

provider(int, double) - Static method in class org.nlpub.watset.graph.MarkovClustering

A factory function that sets up the algorithm for the given graph.

provider(Path, double) - Static method in class org.nlpub.watset.graph.MarkovClusteringBinaryRunner

A factory function that sets up the algorithm for the given graph.

provider(Path, double, int) - Static method in class org.nlpub.watset.graph.MarkovClusteringBinaryRunner

A factory function that sets up the algorithm for the given graph.

provider(Function<Graph<V, E>, Clustering<V>>, Function<Graph<Sense<V>, DefaultWeightedEdge>, Clustering<Sense<V>>>) - Static method in class org.nlpub.watset.graph.SimplifiedWatset

A factory function that sets up the algorithm for the given graph.

provider(Function<Graph<V, E>, Clustering<V>>, Function<Graph<Sense<V>, DefaultWeightedEdge>, Clustering<Sense<V>>>) - Static method in class org.nlpub.watset.graph.Watset

Deprecated.

A factory function that sets up the algorithm for the given graph.

provider(NodeWeighting<V, E>) - Static method in class org.nlpub.watset.graph.ChineseWhispers

A factory function that sets up the algorithm for the given graph.

provider(NodeWeighting<V, E>, int, Random) - Static method in class org.nlpub.watset.graph.ChineseWhispers

A factory function that sets up the algorithm for the given graph.

purity(Collection<Map<V, Double>>, Collection<Map<V, Double>>) - Method in class org.nlpub.watset.eval.NormalizedModifiedPurity

Computes the (modified) purity of the given clusters as according to the gold standard clustering, classes.

R

r - Variable in class org.nlpub.watset.graph.MarkovClustering

The inflation parameter.

random - Variable in class org.nlpub.watset.graph.ChineseWhispers

The random number generator.

REPETITIONS - Static variable in class org.nlpub.watset.eval.Measurer

The default number of repetitions.

run() - Method in class org.nlpub.watset.eval.Measurer

Perform the measurement.

S

sample(T[], Random) - Static method in interface org.nlpub.watset.eval.Sampling

Creates a bootstrapped dataset using sampling with replacement from the given dataset.

Sampling - Interface in org.nlpub.watset.eval

Utilities for statistical evaluation of computational experiments.

score(Map<V, Double>, Collection<Map<V, Double>>) - Method in class org.nlpub.watset.eval.CachedNormalizedModifiedPurity

score(Map<V, Double>, Collection<Map<V, Double>>) - Method in class org.nlpub.watset.eval.NormalizedModifiedPurity

Compute the (modified) cluster score on a defined collection of classes.

score(Graph<V, E>, Map<V, Integer>, NodeWeighting<V, E>, V) - Method in class org.nlpub.watset.graph.ChineseWhispers

Score the label weights in the given neighborhood graph, which is a subgraph of ChineseWhispers.graph.

Sense<V> - Interface in org.nlpub.watset.util

A monad that provides the wrapped value with a sense identifier.

SenseInduction<V,E> - Class in org.nlpub.watset.graph

A simple graph-based word sense induction approach that clusters node neighborhoods.

SenseInduction(Graph<V, E>, Function<Graph<V, E>, Clustering<V>>) - Constructor for class org.nlpub.watset.graph.SenseInduction

Create an instance of SenseInduction.

SEPARATOR - Static variable in interface org.nlpub.watset.util.ABCFormat

The default separator, expressed by the tab symbol.

SEPARATOR - Static variable in interface org.nlpub.watset.util.ILEFormat

The default separator, expressed by the tab symbol.

SimplifiedWatset<V,E> - Class in org.nlpub.watset.graph

A faster and simplified version of Watset that does not need a context similarity measure.

SimplifiedWatset(Graph<V, E>, Function<Graph<V, E>, Clustering<V>>, Function<Graph<Sense<V>, DefaultWeightedEdge>, Clustering<Sense<V>>>) - Constructor for class org.nlpub.watset.graph.SimplifiedWatset

Create an instance of the Simplified Watset clustering algorithm.

SingletonClustering<V,E> - Class in org.nlpub.watset.graph

A trivial clustering algorithm that puts every node in a separate cluster.

SingletonClustering(Graph<V, E>) - Constructor for class org.nlpub.watset.graph.SingletonClustering

Set up the trivial clustering algorithm that puts every node in a separate cluster.

step(List<V>) - Method in class org.nlpub.watset.graph.ChineseWhispers

Perform one iteration of the algorithm.

steps - Variable in class org.nlpub.watset.graph.ChineseWhispers

The number of actual algorithm iterations.

T

TogetherClustering<V,E> - Class in org.nlpub.watset.graph

A trivial clustering algorithm that puts every node together in a single large cluster.

TogetherClustering(Graph<V, E>) - Constructor for class org.nlpub.watset.graph.TogetherClustering

Set up the trivial clustering algorithm that puts every node together in a single large cluster.

top() - Static method in interface org.nlpub.watset.graph.NodeWeighting

A static factory method providing a convenient way to create an instance of TopNodeWeighting.

TopNodeWeighting() - Constructor for class org.nlpub.watset.graph.NodeWeighting.TopNodeWeighting

toString() - Method in class org.nlpub.watset.util.IndexedSense

transform(Collection<Collection<V>>) - Static method in class org.nlpub.watset.eval.NormalizedModifiedPurity

Transform a collection of clusters into a collection of weighted cluster elements.

transform(Collection<Collection<V>>) - Static method in class org.nlpub.watset.eval.Pairwise

Transform a collection of clusters to a collection of pairs generated using 2-combinations of the cluster elements.

transform(Map<V, Number>) - Static method in interface org.nlpub.watset.util.Vectors

Transform the bag-of-words into a real-valued vector.

transform(Map<V, Number>, Collection<V>) - Static method in interface org.nlpub.watset.util.Vectors

Transform the bag-of-words into a real-valued vector.

V

Vectors - Interface in org.nlpub.watset.util

Utilities for mapping bags-of-words to real-valued vectors.

visit(int, int, double) - Method in class org.nlpub.watset.graph.MarkovClustering.InflateVisitor

Raise the value of a single element to the power of r.

visit(int, int, double) - Method in class org.nlpub.watset.graph.MarkovClustering.NormalizeVisitor

Divide the value of a single element by the corresponding column of sums.

W

WARMUP - Static variable in class org.nlpub.watset.eval.Measurer

The default number of warmup runs kept off-record before Measurer.REPETITIONS.

Watset<V,E> - Class in org.nlpub.watset.graph

Deprecated.

use SimplifiedWatset instead.

Watset(Graph<V, E>, Function<Graph<V, E>, Clustering<V>>, Function<Graph<Sense<V>, DefaultWeightedEdge>, Clustering<Sense<V>>>, ContextSimilarity<V>) - Constructor for class org.nlpub.watset.graph.Watset

Deprecated.

Create an instance of the Watset clustering algorithm.

weighting - Variable in class org.nlpub.watset.graph.ChineseWhispers

The node weighting approach.

write(BufferedWriter, Clustering<String>) - Static method in interface org.nlpub.watset.util.ILEFormat

Write the ILE-formatted file representing the clusters.

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