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The S-Space Package is a collection of algorithms for building Semantic Spaces as well as a highly-scalable library for designing new distributional semantics algorithms. Distributional algorithms process text corpora and represent the semantic for words as high dimensional feature vectors. This package also includes matrices, vectors, and numerous clustering algorithms. These approaches are known by many names, such as word spaces, semantic spaces, or distributed semantics and rest upon the Distributional Hypothesis: words that appear in similar contexts have similar meanings.

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/*
 * Copyright 2010 Keith Stevens 
 *
 * This file is part of the S-Space package and is covered under the terms and
 * conditions therein.
 *
 * The S-Space package is free software: you can redistribute it and/or modify
 * it under the terms of the GNU General Public License version 2 as published
 * by the Free Software Foundation and distributed hereunder to you.
 *
 * THIS SOFTWARE IS PROVIDED "AS IS" AND NO REPRESENTATIONS OR WARRANTIES,
 * EXPRESS OR IMPLIED ARE MADE.  BY WAY OF EXAMPLE, BUT NOT LIMITATION, WE MAKE
 * NO REPRESENTATIONS OR WARRANTIES OF MERCHANT- ABILITY OR FITNESS FOR ANY
 * PARTICULAR PURPOSE OR THAT THE USE OF THE LICENSED SOFTWARE OR DOCUMENTATION
 * WILL NOT INFRINGE ANY THIRD PARTY PATENTS, COPYRIGHTS, TRADEMARKS OR OTHER
 * RIGHTS.
 *
 * You should have received a copy of the GNU General Public License
 * along with this program. If not, see .
 */

package edu.ucla.sspace.evaluation;

import edu.ucla.sspace.common.SemanticSpace;
import edu.ucla.sspace.common.Similarity;

import edu.ucla.sspace.util.Pair;

import java.io.BufferedReader;
import java.io.File;
import java.io.FileReader;
import java.io.IOError;
import java.io.IOException;

import java.util.HashMap;
import java.util.HashSet;
import java.util.Map;
import java.util.Set;


/**
 * A simple {@link WordPrimingTest} that extracts priming pairs from a text
 * file.  This text file should have one line for each priming pair where the
 * first the two words are separated by white space.  The first word is the
 * priming cue.  The second word is the priming target.  This class computes
 * priming strength by using the cosine similarity between semantic vectors.
 *
 * @see AbstractWordPrimingTest
 * @author Keith Stevens
 */ 
public class OnePairPerLinePrimingTest extends AbstractWordPrimingTest {

    /**
     * The name of the data file for this test
     */
    private final String dataFileName;
    
    /**
     * Creates a new {@link OnePairPerLinePrimingTest} from a string containing
     * a file name.
     */
    public OnePairPerLinePrimingTest(String testPairFileName) {
        this(new File(testPairFileName));
    }

    /**
     * Creates a new {@link OnePairPerLinePrimingTest} from a {@link File}.
     */
    public OnePairPerLinePrimingTest(File testPairFile) {
        super(prepareRelationMap(testPairFile));
        dataFileName = testPairFile.getName();
    }

    /**
     * Returns a set of prime, target word pairs that are extracted from a text
     * file.
     */
    public static Set> prepareRelationMap(File testPairFile) {
        Set> wordPairSet = new HashSet>();
        try {
            BufferedReader br = 
                new BufferedReader(new FileReader(testPairFile));
            // Each line is expected to contain a space delimited pair of words.
            // The first word is the prime cue and the second word is the target
            // word.
            for (String line = null; (line = br.readLine()) != null; ) {
                if (line.length() == 0 || line.startsWith("#"))
                    continue;
                String[] pair = line.split("\\s+");
                wordPairSet.add(new Pair(pair[0], pair[1]));
            }
        } catch (IOException ioe) {
            throw new IOError(ioe);
        }
        return wordPairSet;
    }

    /**
     * {@inheritDoc}
     */
    protected Double computePriming(SemanticSpace sspace, 
                                    String word1, String word2) {
        return Similarity.cosineSimilarity(
                sspace.getVector(word1), sspace.getVector(word2));
    }

    public String toString() {
        return "Priming Relation: " + dataFileName;
    }
}