edu.ucla.sspace.wordsi

Class WaitingWordsi

java.lang.Object

edu.ucla.sspace.wordsi.BaseWordsi

edu.ucla.sspace.wordsi.WaitingWordsi

All Implemented Interfaces:

SemanticSpace, Wordsi

public class WaitingWordsi
extends BaseWordsi

A Wordsi implementation that performs batch clustering. Each context vector is stored and later clustered using a Clustering algorithm.

Author:

Keith Stevens

Constructor Summary

Constructors

Constructor and Description
WaitingWordsi(Set<String> acceptedWords, ContextExtractor extractor, Clustering clustering, AssignmentReporter reporter) Creates a new WaitingWordsi.
WaitingWordsi(Set<String> acceptedWords, ContextExtractor extractor, Clustering clustering, AssignmentReporter reporter, int numClusters) Creates a new WaitingWordsi.

Method Summary

Methods

Modifier and Type	Method and Description
SparseDoubleVector	getVector(String term) Returns the semantic vector for the provided word.
Set<String>	getWords() Returns the set of words that are represented in this semantic space.
void	handleContextVector(String focusKey, String secondaryKey, SparseDoubleVector context) Adds the context vector to the end of the list of context vectors associated with focusKey.
void	processSpace(Properties props) Once all the documents have been processed, performs any post-processing steps on the data.

Methods inherited from class edu.ucla.sspace.wordsi.BaseWordsi

acceptWord, getSpaceName, getVectorLength, processDocument

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

WaitingWordsi

public WaitingWordsi(Set<String> acceptedWords,
             ContextExtractor extractor,
             Clustering clustering,
             AssignmentReporter reporter)

Creates a new WaitingWordsi. The number of clusters is left unset, which requires that the Clustering algorithm be able to decide on an appropriate number of clusters.

Parameters:

acceptedWords - The set of words that Wordsi should represent. This may be null or empty}.

extractor - The ContextExtractor used to parse documents.

trackSecondaryKeys - If true, cluster assignments and secondary keys will be tracked. If this is false, the AssignmentReporter will not be used.

clustering - The Clustering algorithm to use on each data set.

reporter - The AssignmentReporter responsible for generating a report that details the cluster assignments. This may be null. If trackSecondaryKeys is false, this is not used.

WaitingWordsi

public WaitingWordsi(Set<String> acceptedWords,
             ContextExtractor extractor,
             Clustering clustering,
             AssignmentReporter reporter,
             int numClusters)

Creates a new WaitingWordsi.

Parameters:

acceptedWords - The set of words that Wordsi should represent. This may be null or empty}.

extractor - The ContextExtractor used to parse documents.

clustering - The Clustering algorithm to use on each data set.

reporter - The AssignmentReporter responsible for generating a report that details the cluster assignments. This may be null. If trackSecondaryKeys is false, this is not used.

numClusters - Specifies the number of clusters to generate for each term.

Method Detail

getWords

public Set<String> getWords()

Returns the set of words that are represented in this semantic space.

Returns:

the set of words that are represented in this semantic space.

getVector

public SparseDoubleVector getVector(String term)

Returns the semantic vector for the provided word.

Parameters:

term - a word that may be in the semantic space

Returns:

The Vector for the provided word or null if the word was not in the space.

handleContextVector

public void handleContextVector(String focusKey,
                       String secondaryKey,
                       SparseDoubleVector context)

Adds the context vector to the end of the list of context vectors associated with focusKey.

Parameters:

focusKey - The primary key for contextVector

context - a SparseDoubleVector that represents a single context for a word

processSpace

public void processSpace(Properties props)

Once all the documents have been processed, performs any post-processing steps on the data. An algorithm should treat this as a no-op if no post-processing is required. Callers may specify the values for any exposed parameters using the properties argument.

By general contract, once this method has been called, processDocument will not be called again.

Parameters:

props - a set of properties and values that may be used to configure any exposed parameters of the algorithm.