de.tudarmstadt.ukp.dkpro.core.decompounding.ranking.FrequencyGeometricMeanRanker.java Source code

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/*******************************************************************************
 * Copyright 2010
 * Ubiquitous Knowledge Processing (UKP) Lab
 * Technische Universitt Darmstadt
 *
 * 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 de.tudarmstadt.ukp.dkpro.core.decompounding.ranking;

import java.util.ArrayList;
import java.util.List;

import org.apache.commons.math.stat.descriptive.SummaryStatistics;

import de.tudarmstadt.ukp.dkpro.core.decompounding.splitter.DecompoundedWord;
import de.tudarmstadt.ukp.dkpro.core.decompounding.splitter.Fragment;
import de.tudarmstadt.ukp.dkpro.core.decompounding.splitter.DecompoundingTree;
import de.tudarmstadt.ukp.dkpro.core.decompounding.trie.ValueNode;
import de.tudarmstadt.ukp.dkpro.core.decompounding.web1t.Finder;

/**
 * Frequency based ranking algorithm. See doc folder for more informations.
 * 
 * @author Jens Haase <je.haase@googlemail.com>
 */
public class FrequencyGeometricMeanRanker extends AbstractRanker implements RankerList {
    /**
     * Empty constructor
     * 
     * Use {@link #setFinder(Finder)} before using this class
     */
    public FrequencyGeometricMeanRanker() {

    }

    public FrequencyGeometricMeanRanker(Finder aFinder) {
        super(aFinder);
    }

    @Override
    public DecompoundedWord highestRank(List<DecompoundedWord> aSplits) {
        return rank(aSplits).get(0);
    }

    @Override
    public List<DecompoundedWord> rank(List<DecompoundedWord> aSplits) {
        for (DecompoundedWord split : aSplits) {
            split.setWeight(calcRank(split));
        }

        return filterAndSort(aSplits);
    }

    /**
     * Calculates the weight for a split
     */
    private double calcRank(DecompoundedWord aSplit) {
        SummaryStatistics stats = new SummaryStatistics();
        for (Fragment elem : aSplit.getSplits()) {
            stats.addValue(freq(elem).doubleValue());
        }
        return stats.getGeometricMean();
    }

    @Override
    public DecompoundedWord highestRank(DecompoundingTree aTree) {
        return highestRank(aTree.getRoot(), null);
    }

    @Override
    public List<DecompoundedWord> bestPath(DecompoundingTree aTree) {
        List<DecompoundedWord> path = new ArrayList<DecompoundedWord>();
        highestRank(aTree.getRoot(), path);
        return path;
    }

    /**
     * Searches a a path throw the tree
     */
    private DecompoundedWord highestRank(ValueNode<DecompoundedWord> aParent, List<DecompoundedWord> aPath) {
        if (aPath != null) {
            aPath.add(aParent.getValue());
        }

        List<DecompoundedWord> children = aParent.getChildrenValues();
        if (children.size() == 0) {
            return aParent.getValue();
        }

        children.add(aParent.getValue());
        List<DecompoundedWord> result = rank(children);
        DecompoundedWord best = result.get(0);

        if (best.equals(aParent.getValue())) {
            // None of the childs get a better score than the parent
            return aParent.getValue();
        } else {
            // Find the child node that ranked best and recurse
            for (ValueNode<DecompoundedWord> split : aParent.getChildren()) {
                if (best.equals(split.getValue())) {
                    return highestRank(split, aPath);
                }
            }
        }

        return null;
    }
}