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Java example source code file (WordVectors.java)

This example Java source code file (WordVectors.java) is included in the alvinalexander.com "Java Source Code Warehouse" project. The intent of this project is to help you "Learn Java by Example" TM.

Learn more about this Java project at its project page.

Java - Java tags/keywords

collection, indarray, list, map, serializable, string, util, vocabcache, weightlookuptable, wordvectors

The WordVectors.java Java example source code

/*
 *
 *  * Copyright 2015 Skymind,Inc.
 *  *
 *  *    Licensed under the Apache License, Version 2.0 (the "License");
 *  *    you may not use this file except in compliance with the License.
 *  *    You may obtain a copy of the License at
 *  *
 *  *        http://www.apache.org/licenses/LICENSE-2.0
 *  *
 *  *    Unless required by applicable law or agreed to in writing, software
 *  *    distributed under the License is distributed on an "AS IS" BASIS,
 *  *    WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 *  *    See the License for the specific language governing permissions and
 *  *    limitations under the License.
 *
 */

package org.deeplearning4j.models.embeddings.wordvectors;

import org.deeplearning4j.models.embeddings.WeightLookupTable;
import org.deeplearning4j.models.embeddings.reader.ModelUtils;
import org.deeplearning4j.models.sequencevectors.sequence.SequenceElement;
import org.deeplearning4j.models.word2vec.wordstore.VocabCache;
import org.nd4j.linalg.api.ndarray.INDArray;

import java.io.Serializable;
import java.util.Collection;
import java.util.List;
import java.util.Map;

/**
 * Word vectors. Handles operations based on the lookup table
 * and vocab.
 *
 * @author Adam Gibson
 */
public interface WordVectors extends Serializable {

    String getUNK();

    void setUNK(String newUNK);

    /**
     * Returns true if the model has this word in the vocab
     * @param word the word to test for
     * @return true if the model has the word in the vocab
     */
    boolean hasWord(String word);

    Collection<String> wordsNearest(INDArray words, int top);

    Collection<String> wordsNearestSum(INDArray words, int top);

    /**
     * Get the top n words most similar to the given word
     * @param word the word to compare
     * @param n the n to get
     * @return the top n words
     */
    Collection<String> wordsNearestSum(String word,int n);


    /**
     * Words nearest based on positive and negative words
     * @param positive the positive words
     * @param negative the negative words
     * @param top the top n words
     * @return the words nearest the mean of the words
     */
    Collection<String> wordsNearestSum(Collection positive,Collection negative,int top);

    /**
     * Accuracy based on questions which are a space separated list of strings
     * where the first word is the query word, the next 2 words are negative,
     * and the last word is the predicted word to be nearest
     * @param questions the questions to ask
     * @return the accuracy based on these questions
     */
    Map<String,Double> accuracy(List questions);

    int indexOf(String word);

    /**
     * Find all words with a similar characters
     * in the vocab
     * @param word the word to compare
     * @param accuracy the accuracy: 0 to 1
     * @return the list of words that are similar in the vocab
     */
    List<String> similarWordsInVocabTo(String word,double accuracy);

    /**
     * Get the word vector for a given matrix
     * @param word the word to get the matrix for
     * @return the ndarray for this word
     */
    double[] getWordVector(String word);

    /**
     * Returns the word vector divided by the norm2 of the array
     * @param word the word to get the matrix for
     * @return the looked up matrix
     */
    INDArray getWordVectorMatrixNormalized(String word);

    /**
     * Get the word vector for a given matrix
     * @param word the word to get the matrix for
     * @return the ndarray for this word
     */
    INDArray getWordVectorMatrix(String word);
    /**
     * Words nearest based on positive and negative words
     * @param positive the positive words
     * @param negative the negative words
     * @param top the top n words
     * @return the words nearest the mean of the words
     */
    Collection<String> wordsNearest(Collection positive,Collection negative,int top);


    /**
     * Get the top n words most similar to the given word
     * @param word the word to compare
     * @param n the n to get
     * @return the top n words
     */
    Collection<String> wordsNearest(String word,int n);



    /**
     * Returns the similarity of 2 words
     * @param word the first word
     * @param word2 the second word
     * @return a normalized similarity (cosine similarity)
     */
    double similarity(String word,String word2);

    /**
     * Vocab for the vectors
     * @return
     */
    VocabCache vocab();

    /**
     * Lookup table for the vectors
     * @return
     */
    WeightLookupTable lookupTable();

    /**
     * Specifies ModelUtils to be used to access model
     * @param utils
     */
    void setModelUtils(ModelUtils utils);

}

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