Package weka.filters.unsupervised.attribute

Class TweetToEmbeddingsFeatureVector

java.lang.Object

weka.filters.Filter

weka.filters.SimpleFilter

weka.filters.SimpleBatchFilter

weka.filters.unsupervised.attribute.TweetToFeatureVector

weka.filters.unsupervised.attribute.TweetToEmbeddingsFeatureVector

All Implemented Interfaces:

java.io.Serializable, CapabilitiesHandler, CapabilitiesIgnorer, CommandlineRunnable, OptionHandler, RevisionHandler

public class TweetToEmbeddingsFeatureVector
extends TweetToFeatureVector

An attribute filter that calculates word embedding (word vectors) features for a tweet represented as a string attribute. BibTeX:

 @inproceedings{bravo-marquez16:_deter_word_emotion_assoc_from,
 author = {Felipe Bravo-Marquez and Eibe Frank and Saif M. Mohammad and Bernhard Pfahringer},
 title = {Determining Word-Emotion Associations from Tweets by Multi-Label Classification},
 booktitle = {Proc 15th IEEE/WIC/ACM International Conference on Web Intelligence},
 year = 2016,
 series = {Omaha, Nebraska},
 publisher = {IEEE Computer Society},
 pdf = {http://www.cs.waikato.ac.nz/~eibe/pubs/emo_lex_wi.pdf}
 }
 

Version:

$Revision: 2 $

Author:

Felipe Bravo-Marquez (fbravoma@waikato.ac.nz)

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field	Description
static java.lang.String	RESOURCES_FOLDER_NAME	Default path to where resources are stored.

Constructor Summary

Constructors

Constructor	Description
TweetToEmbeddingsFeatureVector()

Method Summary

Modifier and Type	Method	Description
TweetToEmbeddingsFeatureVector.Action	getAction()
EmbeddingHandler	getEmbeddingHandler()
int	getK()
TechnicalInformation	getTechnicalInformation()	Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
java.lang.String	globalInfo()	Returns a string describing this filter.
static void	main(java.lang.String[] args)	Main method for testing this class.
void	setAction(TweetToEmbeddingsFeatureVector.Action action)
void	setEmbeddingHandler(EmbeddingHandler embeddingHandler)
void	setK(int k)

Methods inherited from class weka.filters.Filter

batchFilterFile, debugTipText, doNotCheckCapabilitiesTipText, filterFile, getCapabilities, getCopyOfInputFormat, getDebug, getDoNotCheckCapabilities, getOutputFormat, getRevision, isFirstBatchDone, isNewBatch, isOutputFormatDefined, makeCopies, makeCopy, mayRemoveInstanceAfterFirstBatchDone, numPendingOutput, output, outputPeek, postExecution, preExecution, run, runFilter, setDebug, setDoNotCheckCapabilities, toString, useFilter, wekaStaticWrapper

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from class weka.filters.SimpleBatchFilter

batchFinished, input

Methods inherited from class weka.filters.SimpleFilter

setInputFormat

Methods inherited from class weka.filters.unsupervised.attribute.TweetToFeatureVector

allowAccessToFullInputFormat, getCapabilities, getOptions, getStemmer, getStopwordsHandler, getTextIndex, getTokenizer, isReduceRepeatedLetters, isStandarizeUrlsUsers, isToLowerCase, listOptions, setOptions, setReduceRepeatedLetters, setStandarizeUrlsUsers, setStemmer, setStopwordsHandler, setTextIndex, setTokenizer, setToLowerCase

Field Detail

RESOURCES_FOLDER_NAME

public static java.lang.String RESOURCES_FOLDER_NAME

Default path to where resources are stored.

Constructor Detail

TweetToEmbeddingsFeatureVector

public TweetToEmbeddingsFeatureVector()

Method Detail

globalInfo

public java.lang.String globalInfo()

Returns a string describing this filter.

Specified by:

globalInfo in class SimpleFilter

Returns:

a description of the filter suitable for displaying in the explorer/experimenter gui

getTechnicalInformation

public TechnicalInformation getTechnicalInformation()

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

Returns:

the technical information about this class

getAction

@OptionMetadata(displayName="action",
                description="The action for aggregating the word embeddings: 1) Average embeddings of the input string (AVERAGE_ACTION),2) Add embeddings of the input string (ADD_ACTION), 3) Concatenate the first *k* embeddings of  the input string (CONCATENATE_ACTION), (default AVERAGE_ACTION).",
                commandLineParamName="S",
                commandLineParamSynopsis="-S <speficiation>",
                displayOrder=6)
public TweetToEmbeddingsFeatureVector.Action getAction()

setAction

public void setAction(TweetToEmbeddingsFeatureVector.Action action)

getK

@OptionMetadata(displayName="k",
                description="Number of words (from left to right) of the tweet whose embeddings will be concatenated.",
                commandLineParamName="K",
                commandLineParamSynopsis="-K <int>",
                displayOrder=7)
public int getK()

setK

public void setK(int k)

getEmbeddingHandler

@OptionMetadata(displayName="embeddingHandler",
                description="The embeddingHandler object to use.",
                commandLineParamName="embeddingHandler",
                commandLineParamSynopsis="-embeddingHandler <string>",
                displayOrder=6)
public EmbeddingHandler getEmbeddingHandler()

setEmbeddingHandler

public void setEmbeddingHandler(EmbeddingHandler embeddingHandler)

main

public static void main(java.lang.String[] args)

Main method for testing this class.

Parameters:

args - should contain arguments to the filter: use -h for help