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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 2009 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.tools;

import edu.ucla.sspace.common.ArgOptions;

import edu.ucla.sspace.mains.OptionDescriptions;

import edu.ucla.sspace.dependency.CoNLLDependencyExtractor;
import edu.ucla.sspace.dependency.DependencyExtractor;
import edu.ucla.sspace.dependency.DependencyTreeNode;
import edu.ucla.sspace.dependency.WaCKyDependencyExtractor;

import edu.ucla.sspace.text.DependencyFileDocumentIterator;
import edu.ucla.sspace.text.Document;
import edu.ucla.sspace.text.TokenFilter;
import edu.ucla.sspace.text.Stemmer;

import edu.ucla.sspace.util.LoggerUtil;

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

import java.util.Collections;
import java.util.Iterator;
import java.util.HashSet;
import java.util.Set;
import java.util.Properties;

import java.util.logging.Level;
import java.util.logging.Logger;


/**
 * @author Keith Stevens 
 */
public class DepSemTokenCounter {

    /**
     * A mapping from token to the number of times it occurred
     */
    private final Set foundTokens;

    /**
     * The {@link DependencyExtractor} used to extract parse trees.
     */
    private final DependencyExtractor extractor;

    /**
     * Creates a new token counter that optionally lower cases tokens
     *
     * @param doLowerCasing {@code true} if the token counter should lower case
     *        all tokens before counting
     */
    public DepSemTokenCounter(DependencyExtractor extractor) { 
        this.extractor = extractor;
        foundTokens = new HashSet();
    }

    public Set getTokens() {
        return foundTokens;
    }

    /**
     * Counts all of the tokens in the iterator
     */
    private void process(Iterator docs) throws IOException {
        long numTokens = 0;
        while (docs.hasNext()) {
            Document doc = docs.next();
            BufferedReader br = doc.reader();
            String header = br.readLine();

            DependencyTreeNode[] nodes = extractor.readNextTree(br);
            int index;
            for (index = 0; index < nodes.length; ++index)
                if (nodes[index].lemma().equals(header))
                    break;

            foundTokens.add(nodes[index].word().toLowerCase());
            for (int i = index+1; i < index+10 && i < nodes.length; ++i)
                foundTokens.add(nodes[i].word().toLowerCase());
            for (int i = Math.max(0, index-10); i < index; ++i)
                foundTokens.add(nodes[i].word().toLowerCase());
        }
    }

    public static void main(String[] args) throws Exception {
        // Setup the argument options.
        ArgOptions options = new ArgOptions();
        options.addOption('F', "tokenFilter", "filters to apply to the input " +
                          "token stream", true, "FILTER_SPEC", 
                          "Tokenizing Options");
        options.addOption('v', "verbose",
                          "Print verbose output about counting status",
                          false, null, "Optional");

        // Parse and validate the options.
        options.parseOptions(args);
        if (options.numPositionalArgs() < 2) {
            System.out.println(
                "usage: java DepTokenCounter" 
                + " [options]   []*\n"
                + options.prettyPrint() 
                + "\n\n" + OptionDescriptions.TOKEN_FILTER_DESCRIPTION);
            return;
        }

        // Setup logging.
        if (options.hasOption("verbose")) 
            LoggerUtil.setLevel(Level.FINE);

        TokenFilter filter = (options.hasOption("tokenFilter"))
            ? TokenFilter.loadFromSpecification(options.getStringOption('F'))
            : null;

        // setup the dependency extractor.
        DependencyExtractor e = new CoNLLDependencyExtractor(filter, null);
        DepSemTokenCounter counter = new DepSemTokenCounter(e);

        // Process each of the input files
        for (int i = 1; i < options.numPositionalArgs(); ++i)
            counter.process(new DependencyFileDocumentIterator(
                        options.getPositionalArg(i)));

        // Then write the results to disk
        PrintWriter pw = new PrintWriter(options.getPositionalArg(0));
        for (String term : counter.getTokens()) 
            pw.println(term);
        pw.close();
    }
}